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PDF - UWA Research Portal
ASSESSING GENERAL MOTOR ABILITY AND TESTS FOR TALENT IDENTIFICATION OF MALAYSIAN ADOLESCENTS By Halijah Ibrahim 0179666 This thesis is presented for the degree of Doctor of Philosophy School of Sport Science, Exercise and Health Faculty of Life and Physical Sciences The University of Western Australia November 2009 ii ABSTRACT Talent Identification (TI) in sports begins by mass screening individuals’ motor abilities. du Randt (2000) wrote that, as test items from one country might not necessarily suit another, appropriate basic motor skill test items are important for developing a TI mass screening instrument. Three hundred and thirty Malaysian adolescents aged from 12-15 years were tested on three motor skill test batteries: the McCarron Assessment of Neuromuscular Development (MAND, McCarron, 1982); the Australian Talent Identification Test (AIS, Australian Sports Commission, 1998); and a Balance and Movement Coordination Test which was specifically developed for this project. In the current research, the motor performance data recorded from the adolescents underwent several types of analyses. Principal Component analyses were conducted on the MAND, AIS and BMC motor skill instruments to understand what the three motor skill instruments were assessing globally in the Malaysian adolescents. Then, first-order and higher-order factor analyses were conducted on the 13 parameters making up the AIS+BMC motor skill instrument to examine the concept of general motor ability (GMA). After descriptive analyses of the adolescents’ motor skill performances, age and gender differences were examined using two (gender) by four (age) ANOVAs. Finally, stepwise discriminant function analyses were conducted on a combined AIS+BMC motor skill instrument to determine the best sub-set of motor skills that reliably classified the Malaysian adolescents into three levels of motor performance. Principal Component analyses on the three motor skill instruments among all participants demonstrated that the MAND assessed three motor abilities - postural control, bi-manual dexterity and muscle power. Only one motor ability was found to be assessed by the AIS motor skill instrument, that of anaerobic power. Finally, the BMC assessed movement coordination, postural control and static balance. These findings did not correspond with the hypothesised factor structures. These instruments need to be carefully examined because what they assess appears to change with the population under investigation. Higher-order factor analyses were performed separately on all subjects to test for a motoric ‘g’. The motor abilities of movement coordination and postural control were found for both girls and boys, and some balancing ability emerged. Girls exhibited static balance, whereas boys recorded a more general balance factor named kinaesthetic integration, and explosive power. Hence, when assessing motor skill, power appears to be relevant for adolescent boys. The descriptive analyses indicated that the participants increased in height, weight and BMI across gender and age. Results also demonstrated no significant interactions between gender iii and age on fine motor skills of the MAND. However, significant interactions between gender and age were shown on the MANDs gross motor skills of grip strength, and fingernose-finger, with varied performances reported for the boys and girls across the age groups. For the gross motor skills of jumping and heel-and-toe the boys outperformed the girls. A gender-by-age interaction was also reported for the AIS motor skill of basketball throw with the older boy and girl age groups throwing further; particularly the 14- and 15-year-old boys. The boys also outperformed the girls for the AIS motor skills of vertical jump and 40m sprint. Finally, a significant interaction between gender and age was reported for the BMC motor skill of hopping speed. This revealed that although boys outperformed girls at age 12 they deteriorated with an increase in age while the girls improved hopping speed as they became older. The two movement coordination motor skills of the shuttle run and the shuttle-run-with-object revealed that the boys outperformed the girls. Finally, the results for the quadrant jump indicated that the number of correct jumps for the girls increased with age and that from age 13 the girls outperformed the boys. Two stepwise discriminant analyses were undertaken to find the best set of motor skills for classifying Malaysian adolescents into three motor coordination groups based on scores on the MAND and three motor ability groups derived from scores on the motoric ‘g’. The ability of a combined AIS+BMC motor skill instrument to classify Malaysian adolescents into the three groups was good for those classified as Normal, not so great for those adolescents classified as High, and poor for those adolescents classified as Low. The motor skills consistently reported across both sets of analyses were Balance-Eyes-Open, BalanceEyes-Closed, Dynamic Balance, Hopping Speed, Quadrant Jump, Hopping-in-Square, Basketball Throw and Shuttle-Run-with-Object. Hence, motor skills assessing static balance, dynamic balance and postural control appeared to reliably discriminate the Malaysian adolescents into three motor performance groups. Finally, an examination of the misclassifications found in the discriminant analyses revealed two things. Those individuals being predicted into a lower group performed a large number of the motor skills to a lesser standard when compared with their correctly classified cohorts. Conversely, those predicted into a higher group performed a number of motor skills to a standard higher than their correctly classified cohorts. Thus, at a global level, certain individuals could be overlooked for further athletic development and is a concern when developing a rigorous TI program. Therefore, practitioners need to be cautious of any single ability score, and how that represents an individual’s athletic potential. These results are discussed, limitations noted, and directions for future research provided. iv ACKNOWLEDGMENTS I would like to thank many people, especially those listed below, without whose contributions this research would not be completed. Firstly, thanks to my research supervisor, Dr. Dawne Larkin for the ideas and enthusiasm shown to me. Your encouragement, guidance and passion constantly inspired me to bring this research area to life. To all the staff and postgraduate students in the School of Sport Science, Exercise and Health, at The University of Western Australia, thanks for all your support and assistance. You provided me with a fantastic environment in which to work. To Dr Paul Heard and Professor Brian Blanksby, special thanks for helping me bring this project to fruition. Thank you Adis for the time you spent helping me with my writing. To Tun and Jem, even though you were far from us, your assistance was the best we had. To Sue, Debbie and the Herdsman Neighbourhood Centre, thanks for being there for us help with the hectic work and release the tension. Thanks too for teaching us how to live in Australia by providing support in the environment and society when we first arrived. Mak, bapak and family, you are my inspirations. Thank you very much to the participants, colleagues and friends in Malaysia, and Universiti Teknologi Malaysia who supported my study here. Most importantly, for my own family, I want to thank my lovely husband and sons, Zainal Fahrul, Faisal and Fauzi for making this thesis possible. Your support and faith make me believe anything is possible. Hopefully, this thesis is reward for all the sleepless nights. v TABLE OF CONTENTS ABSTRACT ....................................................................................................................... ii ACKNOWLEDGMENTS ................................................................................................. iv CHAPTER 1 ........................................................................................................................... 1 INTRODUCTION .............................................................................................................. 1 1.1. STATEMENT OF THE PROBLEM .......................................................................... 3 1.2. RESEARCH QUESTIONS ........................................................................................ 3 1.3. THE CONCEPTUAL FRAMEWORK OF THE STUDY ......................................... 4 1.4. DELIMITATIONS ..................................................................................................... 5 1.5. LIMITATIONS .......................................................................................................... 5 1.6. DEFINITION OF TERMS ......................................................................................... 7 CHAPTER 2 ........................................................................................................................... 9 LITERATURE REVIEW ................................................................................................... 9 2.1. TALENT IDENTIFICATION IN SPORTS ............................................................... 9 2.2. MOTOR ABILITY ................................................................................................... 24 2.3. GENERALITY VERSUS SPECIFICITY OF MOTOR ABILITY ......................... 27 2.4. MOTOR ABILITY TESTS ...................................................................................... 29 2.5. HUMAN MOVEMENT TAXONOMY ................................................................... 31 2.6. FACTORS UNDERLYING MOTOR ABILITY ..................................................... 32 2.7. DISCRIMINATING ITEMS IN MOTOR ABILITY .............................................. 36 2.8. MOTOR ABILITY STUDIES AMONG ADOLESCENTS .................................... 38 CHAPTER 3 ......................................................................................................................... 42 METHODS AND PROCEDURES .................................................................................. 42 3.1. INSTRUMENTS. ..................................................................................................... 42 3.2. TRANSLATION OF TEST INSTRUMENTS INTO MALAY. ............................. 44 3.3. PARTICIPANTS. ..................................................................................................... 45 3.4. ADMINISTRATION OF THE TESTS .................................................................... 46 3.5. DATA ANALYSIS .................................................................................................. 46 CHAPTER 4 ......................................................................................................................... 51 FACTOR ANALYSES OF THE MOTOR SKILL INSTRUMENTS ............................. 51 SECTION A - FACTORS UNDERLYING THE MAND, AIS AND BMC ................... 52 4.1. RESULTS ................................................................................................................. 52 4.2. DISCUSSION: FACTORS UNDERLYING THE MAND, AIS AND BMC.......... 56 4.3. RESULTS – BOYS’ SUB-SAMPLE ....................................................................... 63 4.4. RESULTS – GIRLS’ SUB-SAMPLE ...................................................................... 67 4.5. DISCUSSION – GMA ANALYSES ....................................................................... 70 4.6. GENERAL DISCUSSION ....................................................................................... 73 vi CHAPTER 5 ......................................................................................................................... 77 RESULTS AND DISCUSSION FOR THE MOTOR SKILL PERFORMANCES ......... 77 5.1. AUSTRALIAN INSTITUTE OF SPORT (AIS) TALENT IDENTIFICATION INSTRUMENT ................................................................................................................ 77 5.2. McCARRON ASSESSMENT OF NEUROMUSCULAR DEVELOPMENT (MAND) ................................................................................................................... 84 5.3. BALANCE AND MOVEMENT COORDINATION (BMC) INSTRUMENT ....... 92 5.4. DISCUSSION........................................................................................................... 99 5.5. SUMMARY ........................................................................................................... 110 CHAPTER 6 ....................................................................................................................... 112 DISCRIMINANT ANALYSIS OF COMBINED AIS+BMC MOTOR SKILL SET .... 112 6.1. GROUP CLASSIFICATION BASED ON SCORES ON THE MAND................ 112 6.2. RESULTS – ALL PARTICIPANTS ...................................................................... 114 6.3. DISCUSSION – ALL PARTICIPANTS ................................................................ 120 6.4. GROUP CLASSIFICATION BASED ON THE MOTORIC ‘g’........................... 122 6.5. RESULTS – ALL PARTICIPANTS ...................................................................... 124 6.6. DISCUSSION – ALL PARTICIPANTS ................................................................ 129 6.7. GENERAL DISCUSSION ..................................................................................... 131 SUMMARY, CONCLUSIONS & FUTURE STUDY RECOMMENDATIONS ......... 136 7.1. SUMMARY OF RESEARCH................................................................................ 136 7.2. LIMITATIONS ...................................................................................................... 147 7.3. STRENGTHS ......................................................................................................... 148 7.4. CONCLUSIONS .................................................................................................... 149 7.5. RECOMMENDATIONS FOR FURTHER STUDY ............................................. 150 REFERENCES ................................................................................................................... 151 vii LIST OF TABLES Table 1. Test Items with Predominant Characteristics in the Australian Talent Search Program. ........................................................................................................... 18 Table 2. Different Sets of Items to Identify Talented Young Athletes........................... 19 Table 3. Categorised Factors Underlying Physical Qualities and Motor Educability. ... 35 Table 4. Rate of Motor Ability Improvements. .............................................................. 41 Table 5. Numbers and Percentages of Participants in the Research............................... 45 Table 6. Motor Skills, Scoring Method & Statistical Analyses from Chapters 4-6. ...... 50 Table 7. Correlations, Components & Loadings for the MAND for All Participants. ... 54 Table 8. Correlations, Component & Loadings for the AIS for All Participants. .......... 55 Table 9. Correlations, Components & Loadings for the BMC for All Participants. ...... 56 Table 10. Correlations, Components & Loadings of the AIS+BMC for the Boys........... 64 Table 11. Higher-order Factor Analysis of the AIS+BMC for the Boys. ........................ 65 Table 12. Correlations, Components & Loadings of the AIS+BMC for the Girls. .......... 68 Table 13. Higher-order Factor Analysis of the AIS+BMC for the Girls.......................... 68 Table 14. The First-order Components and Higher-order Factor of the AIS+BMC for the Boys’ and Girls’ Sub-samples. ............................................................. 73 Table 15. Means ± SDs and Reliability Coefficients for the AIS Tests. .......................... 78 Table 16. Means ± SDs for the AIS Anthropometry Measures. ...................................... 79 Table 17. ANOVA Results for the AIS Anthropometry Measures. ................................. 80 Table 18. Descriptives for the Main Effect Age on the AIS Weight Assessment. ........... 80 Table 19. Means ± SDs for the AIS Motor Skills. ........................................................... 82 Table 20. ANOVA Results for the AIS Motor Skills....................................................... 83 Table 21. Descriptives for the Main Effect Age on the Vertical Jump Motor Skill. ........ 84 Table 22. Means ± SDs and Reliability Coefficients for the MAND............................... 85 Table 23. Means ± SDs for the MAND Fine Motor Skills. ............................................. 87 Table 24. ANOVA Results for the MAND Fine Motor Skills. ........................................ 88 Table 25. Decriptives for the Main Effect Age on the Finger Tapping Motor Skill. ....... 88 Table 26. Means ± SDs for the MAND Gross Motor Skills. ........................................... 90 Table 27. ANOVA results for the MAND Gross Motor Skills. ....................................... 91 Table 28. Descriptives for the Main Effect Age on the Jumping Motor Skill. ................ 92 Table 29. Means ± SDs and Reliability Coefficients for the BMC. ................................. 93 Table 30. Means ± SDs for the BMC Body Balance Motor Skills. ................................. 94 Table 31. ANOVA Results for the BMC Body Balance Motor Skills. ............................ 95 Table 32. Means ± SDs for the BMC Movement Coordination Motor Skills.................. 96 Table 33. ANOVA Results for the BMC Movement Coordination Motor Skills. ........... 97 viii Table 34. Mean Heights and Weights ± SDs of the Malaysian Sports Council Data and the Current Research. ............................................................................... 99 Table 35. Number and Percentage of Participants in the Three Motor Coordination Groups. ........................................................................................................... 113 Table 36. Standardised Weights, Structure Canonical Coefficient Values, Potency Index, Canoninical Correlations, Eigenvalues and Group Centroids for the Three Motor Coordination Groups ........................................................ 115 Table 37. Profiling Correctly Classified and Misclassified Observations in the Three- Group Discriminant Analysis for all Participants ............................... 118 Table 38. Participant Numbers & Percentages in the Three Motor Ability Groups. ..... 123 Table 39. Standardised Weights, Structure Canonical Coefficient Values, Potency Index, Canonical Correlations, Eigenvalues and Group Centroids for the Three Motor Ability Groups.................................................................... 125 Table 40. Profiling Correctly Classified and Misclassified Observations in the Three-Group Discriminant Analysis for All Participants............................... 127 Table 41. Summary Table of Findings. .......................................................................... 137 ix LIST OF FIGURES Figure 1. Conceptual framework of motor ability testing & TI program. ......................... 6 Figure 2. Talent identification and the development process. ......................................... 11 Figure 3. The motor skills, loadings & motor abilities for the MAND, AIS & BMC. .... 62 Figure 4. The AIS+BMC motor skills, first-order components and higher-order factor for the boys. ........................................................................................... 67 Figure 5. The AIS+BMC motor skills, first-order components and higher-order factor for the girls. ............................................................................................ 70 Figure 6. Significant age by gender interaction for the Basketball throw. ...................... 83 Figure 7. Significant age by gender interactions for the gross motor skills of Grip Strength and Finger-nose-finger....................................................................... 91 Figure 8. Significant age by gender interaction for the Hopping speed motor skill. ....... 98 Figure 9. The percentile patterns of height among Australian adolescents (Australian Sports Commission, 1998) and Malaysian participants in this study (AG = Australian girls, AB = Australian Boys, MG = Malaysian Girls, MB = Malaysian Boys)........................................................................ 101 Figure 10. The percentile patterns of weight among Australian adolescents (Australian Sports Commission, 1998) and Malaysian participants in this study (AG = Australian girls, AB = Australian Boys, MG = Malaysian Girls, MB = Malaysian Boys)............................................. 102 Figure 11. The percentile patterns for vertical jump results among Australian adolescents (Australian Sports Commission, 1998) and Malaysian participants in this study (AG = Australian girls, AB = Australian Boys, MG = Malaysian Girls, MB = Malaysian Boys)............................................. 104 Figure 12. The percentile patterns for 40m sprint results among Australian adolescents (Australian Sports Commission, 1998) and Malaysian participants in this study (AG = Australian girls, AB = Australian Boys, MG = Malaysian Girls, MB = Malaysian Boys)............................................. 105 Figure 13. The percentile patterns for the multistage fitness test results among Australian adolescents (Australian Sports Commission, 1998) and Malaysian participants in this study (AG = Australian girls, AB = Australian Boys, MG = Malaysian Girls, MB = Malaysian Boys). ....... 106 Figure 14. The percentile patterns for the basketball throw results among Australian adolescents (Australian Sports Commission, 1998) and Malaysian participants in this study (AG = Australian girls, AB = Australian Boys, MG = Malaysian Girls, MB = Malaysian Boys). ....... 107 x LIST OF APPENDICES APPENDIX A Summary of motor ability test instruments APPENDIX B Human Movement Taxonomy APPENDIX C Details for selecting the BMC motor skills APPENDIX D Testing protocols of MAND, AIS and MC test (Malay version) APPENDIX E Letters of permission to conduct data collection APPENDIX F Testing protocols of MAND, AIS and MC test (English version) APPENDIX G Conversion Tables APPENDIX H Confirmatory Factor Analyses of The MAND APPENDIX I Total Sample Analysis Testing Motoric ‘g’ APPENDIX J Female Discriminant Analyses Note. The appendices are stored on the CD provided. 1 CHAPTER 1 INTRODUCTION Talent identification (TI) is a structured process with the goal of maximising personal potential of individuals after revealing exceptional abilities. After being awarded the 1998 Commonwealth Games, the Malaysian Sports Council (Majlis Sukan Negara - MSN) developed a TI and development program to effectively nurture Malaysian athletes. The program tested young participants in sports (Moreland, 1994) and non-sport participants to identify latent sport talent through mass screening tests (Majlis Sukan Negara, 1998). Unfortunately, the concepts and rationales for TI test selection were not documented, except for the test procedures and resultant normative data. After hosting the Games, the program was only continued among athletes and the mass screening of the general population ceased. However, following poor performances in the South-East Asian (SEA) games (1999, 2001, 2003) and subsequent Commonwealth Games (2002, 2006) the MSN, has wanted to recommence the mass screening tests. The development of a national sport institute (Institut Sukan Negara - ISN) in Malaysia was influenced by the Australian Institute of Sport (AIS) (Moreland, 1994) and a talent search program conducted by the AIS motivated Malaysia to follow suit. Because the development of TI instruments and protocols should be population specific (Reilly, Williams, Nevill & Franks, 2000), groundwork is required prior to providing a focused TI program in Malaysia. Talent identification programs in sport require the assessment of individual movement skills through several stages. Firstly, one screens individual organic and motor attributes to assess motor ability. Then follows a phase of sport-specific skills testing and talent development (Australian Sports Commission, 1998; Brown, 2001; Durand-Bush & Salmela, 2001; Grice, 2003; Gulbin, 2001; Hoare, 1995, 1998; Jarver, 1981; Kozel, 1996; Loko, 1994; Malina, 1997; Moore, Burwitz, Collins & Jess, 1998a; Moore et al., 1998b; Regnier, Salmela & Russell, 1993; Riordan, 1987; Wu, 1992). Several countries use similar procedures to identify potentially talented athletes, including Australia (Australian Sports Commission, 1998), China (Wu, 1992), Eastern Europe (Riordan, 1987), Germany (Kozel, 1996) and Russia (Jarver, 1981). Typically, individuals are mass screened via general motor capacity and physical skills, and then sport related skill tests until finally selected for sport development programs (Hoare, 1995; Jarver, 1981). This process assumes that measurable underlying features such as physical type, motor abilities and traits do exist among talented athletes (Regnier et al., 1993). A movement taxonomy 2 was developed (Burton & Miller, 1998) and revised (Burton & Rodgerson, 2001) to point out the importance of specific motor ability (SMA) and general motor ability (GMA) when assessing movement skill. The Burton and Rodgerson (2001) movement taxonomy involves assessment of movement skills at many levels of TI. Thus, when identifying talent in sport, or assessing an individual’s motor ability, one initially assesses various components of physical capacities or abilities such as strength, power, endurance, agility, speed, body coordination, eye-hand and eye-foot coordination, balance and accuracy. Therefore, investigations of the underlying constructs of the motor skill instruments being utilised is essential when assessing TI, because one needs to know what it is that a particular motor skill instrument is assessing. Burton and Rodgerson (2001) also proposed that GMA was the underlying component in movement skill assessment (MSA) at all levels of movement tasks. This includes Movement Skill Sets, Movement Skill and Movement Skill Foundations. The term ‘Movement Skill Foundations’ is used in the taxonomy to refer to motor abilities. Controversy has surrounded the acceptance or rejection of the GMA concept because of inconsistency of results between motor ability items (Burton & Rodgerson, 2001; Chaiken et al., 2000; Rivenes & Sawyer, 1999). The contradictory statistical interpretations are seen when evaluating the factor loading in Fleishman’s studies (1954, 1956 & 1964). Analysis by Rivenes and Sawyer (1999) on the coefficient of determination of Fleishman’s data has lead to a rejection of the GMA concept. However, a re-evaluation of the correlation matrix of Fleishman’s studies has supported the existence of GMA (Chaiken, Kyllonen & Tirre, 2000). In the current research, quite different motor skill test batteries were used to assess different types of motor ability thought to be important for TI in Malaysia. Two of these instruments underwent factor analysis to examine the notion of GMA. However, before developing mass screening TI tests suitable for Malaysia, appropriate test items are needed. Hahn (1991) conducted a series of studies to isolate the most suitable TI instrument specific for rowers. One study validated results of a field test item (arm-and-leg ergometer) with a sophisticated laboratory instrument (rowing ergometer). The selected TI tests were did unearth talented rowers in Australia. Grice (2003) also found some sport specific tests that were useful when selecting talented athletes in specific sports among Americans. However, since there are limited physical capacity and motor ability data available for the Malaysian population (Majlis Sukan Negara, 1998), and given the exploratory nature of the research, the AIS TI test was used in the current research. This was in conjunction with movement coordination and balance motor ability items (BMC) derived 3 to facilitate the development of a Malaysian TI test instrument (Burton & Miller, 1998; Burton & Rodgerson, 2001). Hoare (1994) claimed that the AIS TI test was valid and reliable for Australians. However, whether assessment by the AIS motor skill instrument holds up in the Malaysian context, awaits verification. Additionally, considering the importance of exploring the TI instruments constructs for a specific population, further investigations to identify the factors or motor abilities underlying the TI tests in the current research is required. Finally, an important component to any TI program is the ability to compare individual performances with relevant performance standards. Comparing Malaysian adolescent performances on the motor skills in these instruments with data from other countries will also determine if separate age and gender norms are necessary for Malaysians. 1.1. STATEMENT OF THE PROBLEM The overall purpose of this study was to examine the components of existing motor skill instruments, in conjunction with other basic TI tests in sport, for subsequent use in Malaysia. More specifically, this project: • examined the underlying constructs of the motor skill instruments used here in a sample of Malaysian adolescents; • investigated the existence of a ‘g’ in motor ability or GMA; • compared Malaysian performance data with existing performance data from the West to establish if there is a need to develop norms relevant to Malaysia; • sought to identify the most suitable motor skills from the instruments utilised for inclusion in a TI instrument for Malaysian adolescents; • where possible, examined gender differences 1.2. RESEARCH QUESTIONS In order to address the above purposes, a series of research questions were asked. 1. Do the motor skill instruments developed on Western populations assess the same things when examined on populations in Malaysia, an Eastern culture? Thus, what are the underlying constructs of the motor skill instruments used in this research to elucidate the nature of these instruments in a Malaysian setting? 4 2. Can statistical approaches such as higher order factor analyses provide evidence to support the general motor ability (GMA) concept? 3. Do motor skill performances vary with age and gender among Malaysian adolescents? 4. How do Malaysian participants’ motor performances compare with those reported for Western populations? 5. Can Malaysian adolescents reliably be discriminated and classified into Poor, Normal and High motor coordination groups derived from scores on the MAND, and/or the motor skills in the AIS+BMC motor skill instrument? 6. Can Malaysian adolescents reliably be discriminated and classified into Low, Normal and High levels of motor ability derived from factor scores from the motoric ‘g’ analyses, with the motor skills in the AIS+BMC motor skill instrument? 1.3. THE CONCEPTUAL FRAMEWORK OF THE STUDY Individuals were assessed along a motor ability continuum to identify those exhibiting greater abilities. Assessing persons with high motor ability is an ongoing process at every stage of TI. Fundamental factors which influence sports performance that should be included in any TI program are morphology, motor abilities, perceptual ability, psychological, demographic/situational and socioeconomic levels (Arnots & Gaines, 1986; Bloomfield, 1992; Bompa, 1985, 1990; Malina, 1997; Regnier et al., 1993; Reilly et al., 2000; Woodman, 1985). The research was carried out at the basic level of TI and focused on investigating motor skill variables that helped to identify talented performers. The selection of adolescents aged 12-15 was deemed appropriate because they should have completed the sampling phase and be in the specialising phase of motor skill development. The conceptual framework focused on the underlying constructs or motor abilities assessed by the motor skill instruments employed. The AIS motor skills, together with balance and motor coordination motor skills (i.e., the BMC motor skill instrument), were examined along with a combined AIS+BMC motor skill instrument. In addition, the combined AIS+BMC instrument underwent discriminant analysis to find the best set of motor skills to discriminate and classify participants into three groups based on motor performance ability. Figure 1 illustrates the proposed model on the relationships of motor ability and TI, and the shaded area was the focus of this study. The conceptual framework (Figure 1) illustrates the preliminary factors associated with TI and the continuum of motor abilities specific to the study. The isolation of motor abilities as key factors permitted a two-fold assessment of GMA; firstly as a concept, and then mass screening and motor ability testing required for a population sensitive TI test battery. Thus, 5 this research attempted to find motor skills and motor abilities able to discriminate between general motor performance ability and exceptional motor performance ability in Malaysian adolescents. 1.4. DELIMITATIONS 1. Only two foundations of the eleven movement skill foundations were selected to be examined (Burton & Miller, 1998); namely, balance and movement coordination. Nine motor skills were selected to measure these two movement skill foundations. Thereafter, these nine motor skills formed the motor skill instrument called Balance and Movement Coordination (BMC). 2. Only 330 male and female participants aged 12-15 years participated in the current research. This age range was selected for it was determined to be the most suitable for examining motor performance that could be used for identifying athletic talent. 1.5. LIMITATIONS 1. The field tests could only be conducted either from 8.00-10.00AM or 4.00-6.00PM, as these were the times when physical education classes take place in Malaysia. The average temperature is cooler in the morning than the hotter and more humid afternoons. The temperature and time of day might have influenced participants' performances. 2. Interpretation on the existence of the GMA concept in this study was based on the factor loadings extracted from the first-order factors using higher-order factor analysis. 3. The age groups were limited to 12 – 15 year old adolescents because this represented the ages when Malaysian begin to choose competitive sports. However, it should be noted that, at these ages, biological and chronological ages can vary greatly. 4. Convenience testing was used s access to subjects prevented random stratified sampling. 6 Figure 1. The conceptual framework of motor ability testing and talent identification program. 7 1.6. DEFINITION OF TERMS The following terms were adopted for operational use in this study. Motor Ability Traits or capacities that underlie a variety of movement skill performances. General Motor Ability A trait underlying performance in movement skills (Burton & Rodgerson, 2001; Schmidt & Lee, 1999). Talent Potential physical capacity and trainable motor ability contributing to superior performance in various sport domains. Expertise Individual ability to manipulate biological (physical capacity, motor ability, genetics) and environmental (personality, family, coaching and others) factors through intensive training and obtain excellent performances in various sport domains. MAND McCarron Assessment of Neuromuscular Development standardised test is used to identify individual fine and gross motor skills, especially with poorly coordinated subjects (McCarron, 1982). AIS The Australian Sports Commission (1998) stated that the AIS test instrument assesses four different motor abilities - speed, ability to spring in a vertical direction, upper body strength and aerobic fitness. BMC A motor skill instrument specifically developed for this research to assess two components of Burton and Miller’s (1998) movement skill foundations; namely, balance and movement coordination. 8 NDI score Neuromuscular Development Index score is determined from the total of the standardised scores for each of the MAND tasks. Coordination group Poor, Normal and High groups were determined through the NDI scores from the MAND test, based on their coordination scores. High coordinated group Those achieving an NDI score > 115 in MAND test. Normal coordinated group Those achieving an NDI score from 85-115 in MAND test. Poor coordinated group Those achieving an NDI score < 85 in MAND test. Motor ability group Three groups of participants were determined via the factor score of GMA extracted from a higher order factor analysis of AIS+BMC tests. High motor ability group Individuals who achieve the top 10% of the ‘g’ factor scores among all participants. Normal motor ability group Individuals who achieve from 11% to 89% of ‘g’ factor scores among all participants. Low motor ability group Individuals who achieve the bottom 10% of ‘g’ factor scores among all participants. 9 CHAPTER 2 LITERATURE REVIEW 2.1. TALENT IDENTIFICATION IN SPORTS Attempts to identify talented athletes have operated since organised sport began (Burgess, 1997) and TI is recognised as a key component in successful elite programs (Hoare, 1998). It has evolved from an unstructured process relying on competition results, towards a more systematic and structured approach using evidence-based assessments for TI and development programs. However, using a scientific approach to predict future elite performances is difficult (Regnier et al., 1993) and demands a high work commitment (Gulbin, 2001). Different countries use similar procedures such as mass screening that include general motor capacity and physical tests; followed by sport specific and sport suitability tests; and, finally, a sport specific development program (Hoare, 1995; Jarver, 1981). Previous research has shown that selection test items and criteria used in one country might not be suitable in another (Abbott & Collins, 2002; du Randt, 2000; Viljoen, Malan & Pienaar, 2004). Also, despite similar procedures being utilised by different countries, the motor skill instruments selected as tools for TI are diverse. Performance differences for particular motor skills across different populations has led to the development of tests and norms for individual countries (du Randt, 2000; Viljoen et al., 2004), and each sport has its own specific components (Bompa, 1985; Brown, 2001; Famaey-Lamon, Hebbelinck & Cadron, 1979; Hoare, 2000; Hoare & Warr, 2000; Pienaar & Spamer, 1998; Pienaar, Spamer & Steyn, 1998; Williams & Franks, 1998; Williams & Reilly, 2000). 2.1.1. Talent and Expertise Gagne (1996) claims the concept of talent can have two divergent interpretations. Either it is seen as raw material that is natural ability presented with varying intensity, or as systematically developed abilities which are characteristics of an expert. Within Gagne’s model (1996), the former interpretation is known as giftedness and the latter as talent. Generally, the definition of giftedness almost parallels the definition of motor ability as it refers to one’s innate ability in the sport domain. 10 The giftedness of Gagne’s model is the phase in which mass screening tests for TI programs are significantly involved, and the main focus of this study. Relating the concept of talent in Gagne’s model with TI in sport, TI processes sporting (via a mass screening or talent detection phase) raw material or ‘giftedness’ such as motor ability, perceptual-motor and psychological aspects. Thus, in the talent development phase, one nurtures the raw material to obtain sport expertise by bringing that ‘talent’ to fruition. Both giftedness and talent are inclusive in sport TI. However, the term ‘talent’ is often referred to as raw material. Accordingly, talent has been defined as “any innate capacity that enables an individual to display exceptionally high performance in a domain that requires special skills and training” (Simonton, 1999). In relation to sports, talent can be seen as an undeveloped ability that exceeds the average standard (Williams & Franks, 1998). Individuals who possess talent in sport will exhibit specific characteristics that lead to excellent sporting performance (Williams & Franks, 1998). For the purpose of the current research, similar to the notion of giftedness by Gange (1996), talent will refer to the raw materials that are natural abilities present in an individual. The ultimate goal of a TI program is to maximise sport performance or sport expertise. Expertise is defined as ‘skilfulness by virtue of possessing special knowledge or ability’ (Webnox Corp, 2003). An expert is a person who possesses the raw material, special knowledge or ability to perform skilfully following deliberate practice (Ericsson, 1996; Ericsson & Lehmann, 1996; Richman, Gobet, Staszewski & Simon, 1996; Webnox Corp, 2003). In addition, an expert performance is defined as being consistently superior on a set of tasks which are representative of a specific domain (Ericsson & Lehmann, 1996). As skill is important in sport and acquired through training, expertise consists of a combination of training, experience, and innate differences in capacities and talents (Ericsson & Lehmann, 1996). Gagne’s (1996) interpretation of expertise is referred to as a talent in which expertise is the product of a developmental process of giftedness in a particular domain. 2.1.2. Talent identification process Development and TI programs in sport claim to pursue sports excellence via scientific endeavour (Williams & Franks, 1998; Williams & Reilly, 2000). There is general consensus that TI contains several phases of identification (Australian Sports Commission, 1998; Grice, 2003; Hahn, 1991; Jarver, 1981; Kozel, 1996; Loko, 1994; Majlis Sukan Negara, 1998; Malina, 1997; Matsudo, Rivet & Pereira, 1987; Mohan, 2003; Moreland, 1994; 11 Riordan, 1987; Williams & Franks, 1998; Wu, 1992). The TI and development process comprises the four key phases of detection, identification, selection and development (Williams & Franks, 1998) (Figure 2.) Identification Selection Detection Development Figure 2. Talent identification and the development process. From: Williams, A. M. & Franks, A. (1998). Talent identification in soccer. Sports, Exercise and Injury, 4, 159-165 Within Williams and Reilly’s (2000) model, talent detection involves finding prospective performers who are presently not participating in any sport. Talent detection is based on the prediction of performance with the assumption that measurable underlying factors such as anatomical structure, abilities and traits do exist (Regnier et al., 1993). Talent identification is a process of finding sports participants to train and become elite athletes. Guidance into suitable sports is also provided in this stage (Woodman, 1985). On the other hand, talent selection is a continuous process of identifying athletes who qualify at certain levels of performance. Finally, talent development refers to a stage where potential athletes are exposed to appropriate learning which exploits their potential. Williams and Reilly’s (2000) model indicates that there are different target groups when applying talent detection and TI processes. However, several countries (Australian Sports Commission, 1998; du Randt, 2000; Grice, 2003) combine talent detection (referred to as basic/mass or preliminary screening testing) with the other TI processes to represent a TI program. The current research also uses talent identification as referring to both the talent detection and the TI processes of the Williams and Franks (1998) model. Potential athletes undergo several measurements within the various TI phases. Then, athletes who demonstrate superior results in tests which also predict success in a specific sport, are 12 invited to participate in that sport-specific talent development program. Talent development implies that selected athletes will be placed in a suitable learning environment to maximise their sport potential and be monitored at regular intervals (Williams & Reilly, 2000). Gulbin (2001) affirmed that developing the talent is the more challenging aspect, as both sporting excellence and the person as a whole need to be developed. 2.1.3. Issues in Sports Talent Identification During the 1960s, TI programs were operating in the Russian bloc (USSR) and other countries (Arnots & Gaines, 1986). They were considered to be effective in helping countries with lower populations compete with larger countries to depict the success of their political systems (Arnots & Gaines, 1986). However, the TI contribution to performance enhancement is still controversial (Pienaar, 1998). The practical use of a systematic approach (Williams & Reilly, 2000), ethical and moral issues (Malina, 1997; Pienaar, 1998; Williams & Reilly, 2000); and validity, reliability and objectivity of the tests used to predict performance have been questioned (Durand-Bush & Salmela, 2001). Further, Moore et al. (1998b) wrote that evidence on TI in sport is fragmented and incomplete. The nature of TI is multidimensional (Durand-Bush & Salmela, 2001; Mohan, 2003; Simonton, 1999; Williams & Reilly, 2000). Hence, different approaches have been applied to identify talented athletes (Regnier et al., 1993). It is agreed that factors from sociology, physiology, psychology and anthropometry need consideration. However, their significance also depends on age, type of sport and the development phase in which the prediction of potential athletic success is currently placed (Abbott & Collins, 2002; Burgess, 1997; Malina, 1997; Moore et al., 1998b; Pienaar, 1998; Pienaar & Spamer, 1998; Reilly et al., 2000; Williams & Franks, 1998; Williams & Reilly, 2000; Woodman, 1985). Issues in TI requiring greater clarification Talent - heredity versus environment : The controversial issue of whether talent is largely inherited or the result of training and environment factors, has been widely reported (Ericsson, 1996; Ericsson & Lehmann, 1996; Geladas, Koskolou & Klissouras, 2007; Howe, Davidson & Sloboda, 1998; Simonton, 1999). Although there appears to be an increasing acceptance of the nurture influence over nature (Klissouras, Geladas, & Koskolou, 2007; Simonton, 1999), evidence of the contribution of inherent abilities are explicit in sport. Kutsar (1991) wrote that hereditary anatomical, physiological and psychological prerequisites were important for developing physical performance capacities. This genetic make-up is important in aerobic capacity, adaptability to training (Cowart, 1987), muscle 13 fibre composition (Bompa, 1985; Cowart, 1987; Kutsar, 1991), and personality traits relating to competitiveness and leadership (Cowart, 1987; Plomin, 1989). Strength and power are closely related to body shape, composition, proportionality and posture (Bloomfield, Ackland & Elliott, 1994). Anthropometric measures of height or limb length can be important in sport (Bompa, 1985). Moreover, height and body mass influence biomechanical advantage (Olgun & Gurses, 1984). As weight and blood volume increase exponentially with height, changes in size produced variations in the impact of strength, weight, power output, acceleration and work capacity (Watson, 1995). The interrelationships of these inherent components indicated that body size and shape can be an advantage in different sports. Several studies of twins have demonstrated the contributions of both hereditary and environmental influences on motor performance (Kovar, 1976; Kutsar, 1991; Marisi, 1977; Watanabe, Mutoh & Yamamoto, 2000, 2001; Williams & Gross, 1980). However, not all those with inherited pre-requisite traits actually succeeded when directed into their most appropriate sporting activities (Kutsar, 1991). The influence of environmental factors on motor development and motor ability has long been acknowledged (Branta, Haubenstricker & Seefeldt, 1984; East & Hensley, 1985; Haywood, 1993b; Malina, 1973; Malina & Mueller, 1981; Nelson, Thomas, Nelson & Abraham, 1986; Thomas, 2000; Thomas & French, 1985; Thomas & Thomas, 1988). According to Haywood (1993b), environmental factors such as race, culture, ethnic group, socio-economic status, nutrition and child-rearing practices were probably more influential than genetic factors in motor performance. This was especially so when average, rather than elite, performers were observed. Malina (1973) outlined socio-cultural factors influencing motor development during infancy and early childhood. These were family size, number of siblings, birth order and socioeconomic background; and the opportunity to practise, infant stimulation, and availability of toys and equipment. Several studies found that girls were socialised away from more aggressive competitive activities and boys were socialised into competition (Branta et al., 1984; East & Hensley, 1985; Greendorfer & Lewko, 1978; Haywood, 1993b; Malina, 1973; Malina & Mueller, 1981; Nelson et al., 1986; Thomas, 2000; Thomas & French, 1985; Thomas & Thomas, 1988). Jurimae and Volbekiene (1998) conducted a comparative cross-cultural study of motor abilities between two Baltic countries. Estonian adolescents scored significantly higher in the 20m endurance shuttle-run test, hand grip strength, 10x5m shuttle-run, sit-and-reach, and 14 flamingo balance, than children from Lithuania. On the other hand, the Lithuanian boys scored higher in bent-arm hang than Estonian boys of the same age. Finally, access to facilities, coaching, training and practice are environmental factors that influence individual motor performances. Ericsson and Lehman (1996) argued that deliberate practices were a necessary preparation for one to become an expert performer. Additionally, Ericsson (2007) argues that objectively examining expert performance to identify expert qualities and then devising methods to assess these qualities will be more rewarding than just focusing upon the basic mechanisms that influence an athlete’s development. Thus, since the ultimate goal for identifying talented performers is to maximise that talent into sports expertise, the heredity and environment contributions on athletic expertise must be considered (Baker & Davids, 2007; Button & Abbott, 2007; Simonton, 1999; Singer, 1975). Age of identification: Talent identification and development may take place at various ages, and vary with different sports (Malina, 1997; Williams & Franks, 1998). Some countries start TI and selection of potential athletes at 8-10 years (Tabachnick, 1991), and other countries start screening at 14-16 years old (Australian Sports Commission, 1998). Identifying talented athletes could occur as early as 3-8 years old in sports such as gymnastic, diving, swimming or figure skating, because the peak performances in these sports can occur during adolescence (Malina, 1997). Thus, it appears important to identify talented athletes at young ages so that their success can be enhanced by quality preparation during growth years (Tabachnick, 1991). However, selecting very young participants creates an ethical and moral dilemma. With intensive training at early ages, participants must specialise in a narrow band of activities and skills, and are deprived of exploring other potential abilities. Children should be encouraged to participate in a variety of different activities, and develop a wide range of skills consistent with their interests and their abilities. Cote and Fraser-Thomas (2006) reviewed youth in sport, and suggested that there are many physical, psychological and social benefits to early diversification and some costs to early specialisation. Indeed, Button and Abbott (2007) noted that an athlete’s ability to negotiate critical transitions as they progress through different stages of development could be a critical factor in an athlete’s sporting success (Bloom, 1985; Cote, 1999). Furthermore, there could be implications for 15 growth, nutrition and delay in sexual maturation; and heightened occurrences in adulthood of myocardial dysfunction, depression, psychosocial interactions and heat stress (Committee on Sports Medicine and Fitness, 2000). Predictive items and the construction of test instruments: Generally, a set of anthropometric and physical tests have been used to evaluate all-round performance capacity during the mass screening test phase of TI (Hoare, 1995; Jarver, 1981). Typically, these items do not require sophisticated equipment or specialist assessors (Jarver, 1981), and try to represent a wide range of factors that influence various types of sports performances. Hence, potential sport success could be predicted by identifying the contributing motor abilities. Kirkendall, Gruber & Johnson (1987) stated that motor ability is a general quality able to facilitate future performance in more specific motor tasks. Thus, TI can be used to predict exceptional sporting performance (Howe et al., 1998). However, Moore et al. (1998b) found that no national sport governing bodies in the UK had a TI strategy grounded on a validated, criterion-based performance model. Furthermore, the motor ability constructs being assessed have not been clearly defined and little agreement exists as to the major characteristics for any particular test item (Blomqvist, Luhtanen, Laakso & Keskinen, 2000). Consequently, the test item validity and usefulness, as well as the theoretical constructs upon which they are based, require further study (Durand-Bush & Salmela, 2001). A TI inventory for predicting success was conducted by specific sports associations in the USA for children in grades six, seven and eight (e.g., The Kid Test; Grice, 2003). After developing an inventory focused on aerobic power, motor skills and coordination, data were placed in a working model to identify talent in specific sports. A legend was developed by using the mean and standard deviation to cross reference many sports and calculate a corresponding composite score for each sport. Grice (2003) found relatively high logical validity of performance on various test items across the three grade levels but no significance levels were provided. Grice (2003) also suggested that further research was needed to determine the predictive and concurrent validity, and reliability of the items among adolescents. Predicting superior performances by young children is based on the assertion that skill in sport is associated with the ability to produce a consistent motor pattern (Allard & Burnett, 1985). Another important consideration for TI is that the patterns underlying a particular task can change with age, practice and experience (Schmidt, 1991). Also, variables chosen 16 for TI must have considerable ability to discriminate between performers at all skill levels (Woodman, 1985). Talent is harder to predict in later years because the population of sport performers becomes smaller and more homogeneous, particularly with respect to physical and physiological profiles (Williams & Franks, 1998). According to researchers, it is impossible to accurately predict performance from such tests because of chronological and anthropometric differences among children (e.g., Durand-Bush & Salmela, 2001; Vaeyens, Lenoir, Williams & Philippaerts, 2008). Individual versus team sports: It was first thought that TI programs were effective for individual sports with discrete physical and physiological demands such as athletics, canoeing and rowing. They were considered unsuitable for team sports as they required qualities other than physical and physiological attributes to determine success (Hoare, 1995). Team sport success is often related to players’ knowledge of the game skills and strategies (Allard & Burnett, 1985). Currently, TI research programs for team sports such as soccer (Helsen, Hodges, Van Winckel & Starkes, 2000; Hoare & Warr, 2000; Williams & Franks, 1998; Williams & Reilly, 2000), basketball (Hoare, 2000; Matsudo et al., 1987), volleyball (Matsudo et al., 1987) and rugby (Gibson, Okely, Webb & Royall, 1999; Pienaar et al., 1998) have found that TI programs can be useful. The only reservation is that each sport requires its own specific criteria (tests) that accurately measure attributes contributing to success (Woodman, 1985). Thus, considerable work needs to be done to identify the motor skills that are related to successful performance in a particular sport. 2.1.4. Talent Identification in Malaysia A TI program in Malaysia was in place prior to hosting the Commonwealth Games in 1998. The TI test procedures and normative data for Malaysian adolescents aged 11-14 years, and Malaysian elite athletes were published but no other information was available (Majlis Sukan Negara, 1998). No documented concepts or groundwork on the TI tests or related matters are available. The test items were height, arm span, sitting height, body mass, skin fold measurements, weight throw, vertical jump, 40m sprint, agility hexagon test, and endurance shuttle run or an 800m run. As Malaysian international sport performances have diminished, the Ministry of Youth and Sport has sought to overcome past problems and reconvene the TI mass screening. 17 2.1.5. Talent Identification Testing in Australia Australia has a well established TI program in sports (Australian Sports Commission, 1998). The mass screening phase is called the Talent Search Program to identify and prepare potentially talented athletes for domestic, national and international competitions. The assessment measures are height and sitting height, body mass, arm span, basketball throw, vertical jump, 40m sprint and shuttle run (multi-stage fitness test). Three test items are anthropometric in nature while the other four measure aspects of motor performance. Several tests have been developed for phase two, depending on the sports under consideration (Australian Sports Commission, 1998). Each of the four motor performance tests measures an individual’s specific athletic capability. The motor performance tests have different characteristics and measure different aspects of motor ability (see Table 1). Test items in the mass screening testing phase of the Australian Talent Search program have different predominant characteristics than those used to measure individual capabilities in phase two. In some cases, the same test items might be used but with different purposes in mind. In addition, to date, there was no evidence outlining the degree to which the individual test items discriminated between talented youngsters. 2.1.6. Differences in Items Used in Talent Identification Test Batteries Researchers in several countries have devised different motor performance tests to identify talented young athletes in different sports (see Table 2). In general, these tests measure individual strength, endurance, power, agility and speed. However, despite some similarities in the types of tests used in different nations, one country’s test items and criteria might be unsuitable in another country (du Randt, 2000; Viljoen et al., 2004). For example, a consideration of gender dis/advantage and urban/rural area distribution factors revealed that 78% of the relevant test performances were significantly different for adolescents in Australia and South Africa. Hence, when using tests developed in another country, such tests need to be validated first on the population under consideration prior to their adoption based solely on theoretical grounds. 18 Table 1. Test Items with Predominant Characteristics in the Australian Talent Search Program. Test Items Predominant Characteristics Vertical Jump Ability to spring in a vertical direction (Australian Sports Commission, 1998). Motor Explosiveness (Larson, 1941). Test of Power, Strength, Speed, Energy, Dexterity (McCloy, 1968). Explosive Strength (Fleishman, 1964; Sargent, 1968) Power (Johnson & Nelson, 1986). Shuttle Run (Multi- Aerobic fitness (Australian Sports Commission, 1998; Jurimae & stage fitness) Volbekiene, 1998; Leger & Lambert, 1982; Tomkinson, Olds & Gulbin, 2003). 40 m Sprint Speed (Australian Sports Commission, 1998; Johnson & Nelson, 1986; Safrit, 1995). Basketball Throw Upper body strength (Australian Sports Commission, 1998). Strength and/or Coordination (Barrow & McGee, 1964). Muscular Strength & Speed of Movement (Arnheim & Sinclair, 1979). Arm & shoulder coordination (Barrow, 1954). Height and Sitting Motor capacity Height Body Mass Motor capacity Arm Span Motor capacity 19 Table 2. Different Sets of Items to Identify Talented Young Athletes. Articles/Reports Sets of Test Items Age Groups Australian Talent Phase 1: Remarks 12-17 years For mass screening Identification Basketball throw (upper body old Program strength), Vertical jump (ability to (Australian spring in a vertical direction), 40-m Sports sprint (speed), Shuttle run - multi- Commission, stage fitness test (aerobic fitness) tests. 1998). Australian Talent Phase 2: Athletics, baseball, Identification Counter Program explosiveness), (Australian (ability to spring in a vertical diving, hockey, Sports direction), Cricket ball throw (arm judo, netball, Commission, speed), Radar speed (over arm rowing, rugby, skiing, soccer, 1998); (Hoare, throwing 2000; Hoare & throw Warr, 2000). Seated movement jump Vertical speed), (general shot (leg 12-17 years basketball, jump old Forward shot explosiveness), throw (body canoeing, cycling, softball, swimming, tennis, explosiveness), Basketball throw triathlon, (upper body strength), Bench pull volleyball, (arm and shoulder strength), Agility polo, weightlifting run (agility), 20 and 40 meter sprint and wrestling. water (ability to accelerate), 20 meter fly (ability to accelerate), Multistage fitness test (aerobic fitness), Arm/leg ergometer (aerobic power) Brazil (Matsudo 50m dash, 40s run, Vertical jump 7-18 et al., 1987) USSR 1981) years Talent (without arm assist), Vertical jump old identification (with arms), Long jump, Shuttle run assessment. (Jarver, 30 m from standing start (speed), 8-14 12/15 min run (endurance), Harvard old step tests (work capacity), Standing long jump (power) years Basic selection. 20 Table 2 continued. KidTest USA Body fat, standing long jump, 15 Grade 6, 7 Talent (Grice, 2003) Estonian yard shuttle run, 40 yard dash, and 8 identification throw, catch, kick and run inventory. Talent 30 m sprint from standing start, 10 s Not reported selection maximal speed running on the sport, procedures 3 x 10 m shuttle run, 5-minute run, (Loko, 1994) Standing long jump, Vertical jump, The preliminary selection phase. Medicine ball throw with two hand from sitting position, Pull-ups, Push-ups, Flexibility. Rugby Union – Strength, Aerobic fitness, 12-17 Coach checklist had Australia (Gibson Balance whilst running with ball, years old been used to identify et al., 1999) Speed, Agility, Power, rugby union individual skill attributes Acceleration, Flexibility Soccer - UK 20 m progressive run tests (aerobic 15-17 Talent identification in (Reilly et al., performance), 5, 15, 25, 30 m years old soccer. 2000) sprints (anaerobic performance), 40m sprints with turn (agility), Repeated sprints (speed endurance), Vertical jump (power). Swimming – Height and weight, grip strength, Canada (Poppleton Salmoni, 1991) shoulder, trunk and ankle flexibility & 8-17 Involving other years old instruments – swim performance, perceived competence, family sport history and status. maturational 21 Specifically, the two motor ability constructs of balance and movement coordination were examined along with previously developed TI tests from Australia’s Talent Search Program (Australian Sports Commission, 1998). The selection of balance and movement coordination components from the Movement Skill Foundations Checklist by Burton and Miller (1998) was based upon their strong evidence regarding the importance of balance and coordination in skilled sporting performances. Balance: The inclusion of balance in many motor ability tests is indicative of its importance in movement skill proficiency (Burton & Miller, 1998). Balance is generally described as either static or dynamic (Bass, 1939). Static balance involves maintaining a position while the body is stationary, whereas dynamic balance involves maintenance and control of body posture when moving. Both kinds of balance also have been related to general motor ability or GMA. Willgoose (1961) and Bass (1939) indicated that dynamic balance reflected the strongest relationship with talented participants. Balance was included here because there are no specific items of balance in the Australian TI test. The balance tasks contain interactive effects of visual control, kinaesthetic senses, body sway and base of support during upright stance. Including these items ensures that visual control will either separate or merge these balance factors together. It also provides the opportunity to construct pre-constructional aspects of postural control or postural stability within motor ability. The pre-construction of postural control should be considered because balance and postural control are more frequently viewed as synonymous terms (Burton & Davis, 1992; Burton & Miller, 1998; Kollmitzer, Ebenbichler, Sabo, Kerschan & Bochdansky, 2000; Slobounov & Newell, 1994; Westcott, Lowes & Richardson, 1997). Coordination: Coordination is the ability to integrate the various parts of a body’s muscular, motor and sensory systems, and the environment; without unnecessary tension, and in proper sequence to perform movement skills harmoniously and rhythmically. Movement coordination is a cooperative interaction of the neuromuscular system (Tittel, 1988) where groups of muscles are patterned or programmed within the integrative processes of the CNS to work sequentially in a smoothly timed manner (Barrow & Brown, 1988). Coordination reflects an ability to perform movements of various degrees of difficulty very quickly, precisely and efficiently (Bompa, 1990). Barrow (1977) indicated that levels of coordination reflect the ability of an individual to integrate all types of movements into specific patterns. 22 Coordination is a complex bio-ability (Bompa, 1990) and is closely interrelated with agility, balance (Barrow, 1977), speed (Barrow, 1977; Bompa, 1990), flexibility (Bompa, 1990), relationships of kinaesthetic sense; with the learner’s perceptions (Barrow, 1977; Barrow & McGee, 1979), strength and endurance (Bompa, 1990). Broer (1973) inferred that coordination consisted of timing the control of body parts and rhythmic movements which involve speed, sequence and duration; and muscular control of voluntary movement sequences which involve force, speed, direction and range of muscle contractions which adapt easily to the purpose of the movement. Thus, coordination is the combining of simple movements without unnecessary tension and in proper sequence to make a smooth complex movement (Broer, 1973), and motor skills specifically designed to assess movement coordination were included in the current research. 2.1.7. Sport Expertise Sport expertise studies were influenced by the development of cognitive science and cognitive psychology (Feltovich, Prietula & Ericsson, 2006), and by cognitive and perceptual-motor skills (Ericsson & Lehmann, 1996). Generally, studies focused on the factors, stages and process that influenced the development of sport expertise (Abernethy, 2005). Sports expertise is defined as consistently superior athletic performance over an extended period (Starkes & Allard, 1993). The purpose of conducting talent detection, identification, selection and development in sport is to produce experts in specific sports. Several factors influencing sport expertise, including nature versus nurture, and biological and environmental contributions, are still matters of debate. Some research has found that deliberate practice is more influential than innate talent, having reported significant correlations between the hours of specific sport practice and levels of attainment (Baker, Cote & Abernethy, 2003; Baker, Horton, Robertson-Wilson & Wall, 2003; Ericsson, Krampe & Tesch-Romer, 1993; Helsen et al., 2000; Helsen, Starkes & Hodges, 1998; Hodges & Deakin, 1996; Hodges & Starkes, 1996; Starkes, 2000; Starkes, Deakin, Allard, Hodges & Hayes, 1996). Others have maintained that heredity is just as important in responses to training (Baker, 2001; Baker & Horton, 2004; Bouchard et al., 1999; Bouchard et al., 1998; Bouchard, Lykken, McGue, Segal & Tellegen, 1990; Hopkins, 2001; Maes et al., 1996; Rankinen et al., 2001, 2002). Extending these issues into empirical studies, Baker and Horton (2004) divided items that could influence sport expertise into primary and secondary factors. Primary factors directly influence acquisition of expert performance and include genetics, training and psychological 23 factors. The secondary factors were socio-cultural and contextual elements (Baker & Horton, 2004). Delineation of nature and nurture is an important step in considering talent holistically, and would hopefully enable more complete approaches to future motor ability research. A heightened awareness of the need to examine sports expertise has led to current investigations becoming more varied. Studies previously focused on individual differences in perceptual-motor and information processing abilities, but now include other areas such as sports expertise concepts in the TI and development processes (Abernethy, 1990, 1991; Abernethy & Wood, 1999; Allard, Graham & Paarsalu, 1980; Allard & Starkes, 1980; Starkes, 1987; Williams, Davids, Burwitz & Williams, 1994). Assessments of individuals with talent, together with practice over a certain period of time, and based on the requirement of that sport’s domain, are important to produce high performers in sport. Hence, TI attempts to match innate or learned features in a given sport to maximise the probability of finding exceptional athletes (Regnier et al., 1993). Talent or ability recognition requires complex interactions, is dependent on environmental conditions, is partially innate and internal, and acknowledges that different motor abilities underlie motor performances in different sports (Williams & Franks, 1998). The notion that motor ability underlies motor performance demonstrates the need to investigate the types of motor ability being assessed by the motor performance tests in TI programs. The success or failure of TI programs also depends upon matching a person’s ability with the demands of the sport (Malina, 1997). At the upper levels of TI programs, other factors such as experience, training, anticipation, game skills and ability to read the game become increasingly essential because, generally, no significant differences in motor ability are shown at the elite level (Allard & Burnett, 1985; Helsen et al., 2000; Starkes, 1987). Furthermore, there is evidence of maximal adaptation to task constraints through deliberate practice (Ericsson & Lehmann, 1996) and the element of enjoyment (Helsen et al., 2000) which contributes to exceptional performance. To summarise, the TI process has highlighted several issues surrounding talent identification. The age of identification and the influence of both hereditary and environmental factors need careful consideration. Also, more research is required to identify motor skills related to successful performance in particular sports. The Australian TI model was adopted by Malaysia to identify their talented sporting individuals but concerns have been raised regarding the validity of their motor skill assessment in populations outside 24 Australia. Given a resurgence of interest in the TI program in Malaysia, the current research sought to examine the Australian motor skill assessment more closely; along with other motor skills which assess basic fundamental movement skills not assessed by this instrument, for subsequent use in TI in Malaysia. Finally, TI is the first important step in the development of sport expertise. However, there is an assumption that experts in particular sports exhibit specific motor abilities that are associated with those sports. Thus, not only is it important to assess individuals’ motor performances using a variety of motor skill instruments, it is also important to understand what motor abilities these instruments are assessing. The rest of this chapter will review literature on motor ability. 2.2. MOTOR ABILITY Many motor ability tests exist with various rationales and objectives for different age groups, and contain different test items. The final selection of these items has been through correlation analysis (Brace, 1927; Carpenter, 1940; McCloy, 1937), factor analysis (Alden, Horton & Caldwell, 1932; Bruininks, 1978; Larson, 1941); or a combination of item difficulty, item discrimination and correlation studies (Henderson & Sugden, 1992). In addition, the selection of test items is based on different classification systems of motor abilities and movement skills (Burton & Miller, 1998; Irvine, 1951). Through the development of motor ability tests, studies relating to generality and specificity have been conducted. The generality of motor ability (GMA) refers to the ability underlying more specific abilities. Specific motor ability (SMA) refers to an ability that reflects a characteristic from similar motor abilities. However, issues surrounding generality versus specificity have disrupted further developments of general motor ability tests. The acceptance or rejection of the concept of GMA is typically based upon interpretation at the inter-correlational level (Burton & Rodgerson, 2001). The low and inconsistent levels of inter-correlations reported in research (Burton & Davis, 1992; Drowatsky & Zuccato, 1967; Fleishman, 1964; Harris, 1969; Rivenes & Sawyer, 1999) and review articles (Alderman & Howell, 1969; Bachman, 1961; Battinelli, 1984; Henry, 1958, 1968; Macintosh, 1974; Oxendine, 1967) has led to some doubts regarding the GMA concept. However, Darlington (2002) wrote that such findings need not necessarily indicate that the data fail to support the existence of GMA and fit the hypothesis, but merely show that the variables analysed have little in common with each other. These statements suggest that, 25 whilst there is low common variance in composite scores and within-task correlations, these discrepancies represent the GMA concept. Although extensive research on the GMA concept by Fleishman (1954) was conducted 50 years ago, more recent re-examinations of Fleishman’s data have led to either an acceptance (Chaiken, Kyllonen & Tirre, 2000) or rejection (Rivenes & Sawyer, 1999) of the GMA concept. Thus, if GMA is to become a part of movement skill assessment taxonomy, it needs further research when an opportunity arises (Burton & Rodgerson, 2001). This study afforded such an opportunity. Barrow (1977) indicated that general qualities of individuals have been divided into motor capacity, motor ability, motor educability and motor fitness. A major focus in this study was motor ability. However, to understand the precise nature of these general qualities, each is defined to clarify the terminology adopted by this project. 2.2.1. Motor Capacity and Motor Ability Motor capacity and motor ability nomenclature in movement assessment can be confusing because both examine body development through the total performance of the individual (Irvine, 1951). Differentiation between the underlying concepts of motor capacity and motor ability is not clearly described and, while the term motor ability has been described extensively, motor capacity has not. Motor capacity has been defined as a wide-ranging quality which demonstrates individual innate ability or potential to perform complex motor skills (Barrow, 1977; Irvine, 1951; Johnson & Nelson, 1986; Philips & Wendler, 1950). McCloy (1934b) identified four indicators of individual motor capacity; namely, size and maturity, power, motor educability, and agility and coordination. Motor ability entails traits or capacities of an individual when performing a variety of movement skills (Burton & Miller, 1998; Burton & Rodgerson, 2001; Fleishman, 1964; Magill, 1993; Sage, 1984) that are innate and acquired (Johnson & Nelson, 1986), and stable over a long period of time (Barrow, 1977; Keogh & Sugden, 1985). These definitions suggest that both concepts have similarities and are important components of motor performance. The difference is that motor capacity is specific to an individual's innate ability, whereas motor ability is regarded as both an innate and acquired (developed) capacity (Irvine, 1951). In addition, motor ability is an indication of an individual’s performance level, while motor capacity refers to an individual’s innate potential for motor skills (Philips & Wendler, 1950; Willgoose, 1961). 26 2.2.2. Motor Educability and Motor Fitness Motor educability is the ability to learn new skills rapidly (Baumgartner & Jackson, 1991; Philips & Wendler, 1950). Barrow (1977) stated that motor educability implies that speed and rate of learning motor skills will differentiate an individual’s level of motor performance. Motor educability is related to maturation, size, physique and most of the factors listed under components of movement (speed, power, balance, flexibility, hand-eyefoot-eye coordination, coordination, kinaesthetic sense and accuracy), but very little to strength and endurance (Barrow, 1977). Baumgartner and Jackson (1991) claimed that the motor educability concept gained ground with developments in the field of intelligence. Therefore, motor educability is sometimes called motor intelligence (Willgoose, 1961). Motor fitness is the ability to perform basic motor skills involving elements of power, agility, speed and balance (Johnson & Nelson, 1986). It is similar to motor ability only in that motor fitness refers to individual traits or capacities that are heavily weighted towards excessive stress and fatigue (Barrow, 1977). In addition, motor fitness rapidly improves with training and conditioning (Burton & Miller, 1998; Clarke & Clarke, 1987; Johnson & Nelson, 1986; Keogh & Sugden, 1985). Thus, when describing movement behaviour, these general qualities tend to be used interchangeably. Given the interrelated nature of the four qualities, one can understand why confusion exists with their use. However, they are qualitatively different and each should be used with care. This study focused on motor ability as it refers to the level of innate individual traits for performing a variety of movement skills. 2.2.3. General Motor Ability (GMA) General motor ability is an aptitude for doing many different motor performance things (Willgoose, 1961). Specific to movement behaviour, GMA is a common factor that enables certain individuals to perform well, or to quickly acquire a high level of proficiency, on any motor task (Sage, 1984). Barrow and McGee (1964) defined GMA as the presently acquired, innate ability to perform motor skills of a general or fundamental nature. Schmidt and Lee (1999) refer to GMA as a single trait of a person that underlies performance in all movement skills. Sometimes, GMA is recognised as the general athletic ability enabling one to excel in sport (Barrow, 1977; Campbell & Tucker, 1967; Johnson & Nelson, 1986). 27 Two important components of GMA are ability and skill. General descriptions of these terms are included to avoid any switching of terms in this study. Ability is an individual trait underlying the performance of motor skills (Magill, 1997; Schmidt & Lee, 1999). Skill requires voluntary body and/or limb movements to achieve a specific goal (Magill, 1997) that results in maximum certainty with minimum outlay of time and energy (Guthrie, 1952). Abilities are more general, and underlie simple and complex tasks; while skills are more specific and narrow, and involve complex tasks (Henry & Hulin, 1989; Magill, 2001). Motor abilities are the foundations for acquiring skills rapidly; and such skills are learned through practice and rely on the presence of inherent abilities (Sage, 1984). 2.3. GENERALITY VERSUS SPECIFICITY OF MOTOR ABILITY The concept of GMA is related to that of general intelligence, or ‘g’, in human psychology (Kirkendall, Gruber & Johnson, 1987; Sage, 1984). Although still controversial, the ‘g’ factor has survived extensive investigation and is widely accepted (Aluja-Fabregat et al., 2000; Caroll, 1993; Colom et al., 2000; Detterman & Daniel, 1989; Jensen & Weng, 1994; Johnson et al., 2004). Johnson et al. (2004), investigated the ‘g’ question from three different perspectives. The first related to the ‘g’-loading on mental ability tests and the stability of a test when inserted into other sets of tests. Secondly is the degree to which the ‘g’ loadings for tests depend on the particular method of factor analysis used to extract the ‘g’ factor. The third perspective relates to the consistency of the ‘g’ factor from one mental ability test battery to another. Johnson et al. (2008) set out to replicate this finding in another sample by examining five cognitive test batteries. Again, a second-order confirmatory factor analytic approach of the test batteries was undertaken. Initially, exploratory factor analyses were performed on each of the batteries in order to develop second-order factor models independently. From the firstorder analyses, several independent ‘g’ factors were found for each battery. Then, the second-order confirmatory analysis found correlations between the five ‘g’ factors ranged from .77 to 1.00 which indicated that the concept of ‘g’ as a unitary construct was evident. The GMA is a complex concept which maintains that an individual has the ability to perform a broad spectrum of activities (Clarke & Clarke, 1987). Also, the GMA assumes an integrated composite of individual strength, endurance, power, speed, agility, balance, reaction time and coordination that underlie performances in various complex motor skills; as well as other physical, mental, emotional and social domains. The principle of generality 28 maintains that one could measure motor ability by simply measuring the height of a vertical jump (Sargent, 1921, 1968). The notion was that a superior GMA would enable one to perform well on any motor task (Burton & Rodgerson, 2001; Schmidt & Lee, 1999). Other studies developed tests of motor ability to either classify students homogeneously for physical education classes or to evaluate general athletic performance (Alden et al., 1932; Brace, 1927; Carpenter, 1942; Cozens, 1929; Garfield, 1924; Humiston, 1937; Johnson, 1932; Kistler, 1937; McCloy, 1938; Powell & Howe, 1938, 1939; Scott, 1939, 1943). Brace (1927) conducted 20 gross motor stunt tests of varying difficulty to measure individual ability and suggested that these tests could classify students for physical education classes. Cozens (1929) measured the general ability of college men and found that physical skill test items adequately measured athletic ability. Also, he suggested that GMA was composed of seven components of motor ability: (i) arm and shoulder coordination with implements, (ii) arm and shoulder girdle strength, (iii) hand-eye, foot-eye and arm-eye coordination, (iv) jumping, or leg strength and flexibility, (v) endurance or sustained effort body coordination, (vi) agility and control; and (vii) speed of legs with coordination of the body. By comparison, Barrow (1954) developed a motor ability test for college men. He recommended two test batteries for predicting GMA and identified eight underlying components: (i) arm and shoulder coordination, (ii) flexibility, (iii) power, (iv) hand-eyefoot-eye coordination, (v) speed, (vi) strength, (vii) balance and (viii) agility. Magill (2001) reported how different scholars have different notions of what actually constitutes motor ability. Some agree with the notion of GMA underlying movement tasks and performances, while others believe in specific motor ability (SMA). Controversy over GMA versus SMA has arisen because of disputes regarding how they relate to one another in the same individual (Magill, 2001). Further, there is disagreement regarding data interpretation, and inconsistent use of terms and constructs (Burton & Rodgerson, 2001). Interest in motor tests of generality was strongest between 1930 and 1960 (Baumgartner & Jackson, 1975), but a change to specific tests was driven by Henry’s Specificity Hypothesis (Henry, 1958, 1968). The theory of motor specificity was based upon the low intercorrelations found between various motor performances (Burton & Rodgerson, 2001; Henry, 1958, 1968; Seashore, 1942). The general motor tests did not adequately predict many different tasks on the basis of a single or limited number of test items (Bachman, 1961; Burton & Davis, 1992; Macintosh, 1974; Schmidt & Lee, 1999). The SMA theory considered that abilities were largely independent (Henry, 1958, 1968; Magill, 2001), taskspecific (Henry, 1958, 1968; Hensley & East, 1989); and that motor transfer between them 29 was generally low and positive (Schmidt & Lee, 1999). Evidence supported the concept of SMA due to the low inter-correlations found between different reaction time and movement time tasks (Henry, 1961; Loockerman & Berger, 1972), balance tasks (Burton & Davis, 1992; Drowatsky & Zuccato, 1967), throwing and kicking tasks for accuracy (Singer, 1966), and strength tasks (Loockerman & Berger, 1972). The low correlation coefficients suggested that the above-mentioned abilities were task specific, rather than representative of GMA . Fleishman (1957) suggested that motor ability was general at first but became more specific with practice. The instructional strategy either supports or refutes generality of ability depending upon the individual learning stage. Specificity emerges as the skill elements come together with greater practice. Fleishman’s (1958a) suggestion was evident in a study of 24 fine motor ability items which found low correlations between variables. He concluded that abilities were specific in nature, non-transferable and task-specific. Briefly, task generality or specificity needs further clarification via theoretical reasoning and research evidence, because task and ability are not the same thing (Barrow, 1977). By their nature, tasks are specific while ability is broader in scope. In addition, ability could be more general because it includes different movement patterns rather than just an isolated task. The GMA hypothesis claims that many different motor abilities of an individual are highly related and can be characterised in terms of singular or global motor ability (Magill, 2001). As motor abilities were usually identified through correlations or factor analyses, it was assumed that the inter-correlations between the wide ranges of different motor abilities would be fairly high. But, the statistical analyses of correlation, factor analysis, and higher order and hierarchical factor analysis have resulted in correlation coefficients ranging between 0.40 and 0.50 (Detterman & Daniel, 1989; Thorndike, 1987). However, Burton and Rodgerson (2001) claimed that rejecting the GMA because of low correlations may not be valid and should be re-evaluated. Despite low correlation coefficients, the factors in motor ability can still be related and further investigations of the GMA construct should be continued using methodologies capable of identifying ‘g’. 2.4. MOTOR ABILITY TESTS Inspired by the general ability and intelligence concept, some physical educators consider that individuals possess an inherent level of GMA and motor intelligence to perform motor activities (Willgoose, 1961). Recognising the need to assess individual levels of GMA and motor intelligence, motor behaviour researchers have developed several standard tests of 30 motor ability. The purpose of motor ability measurement is to determine individual proficiency in specific movement skills and assess the factors that underlie a broad range of motor skills. Historically, the first motor ability test battery was reported in 1912, The Sigma Delta Psi Test (Clarke & Clarke, 1987); and was continuously modified until the 1950s. During this time, the motor ability tests were used to apportion physical education classes into homogeneous groups (Alden et al., 1932; Barrow, 1954; Humiston, 1937; Johnson, 1932; Kistler, 1937; Powell & Howe, 1938, 1939; Scott, 1939, 1943). Those instruments used a single index or composite score to interpret individual GMA. The concept was that one who learned and performed certain skills easily, would learn and perform others equally well (Oxendine, 1967). Since then, research of motor ability instruments has used different perspectives and research methodologies. However, the emergence of the SMA theory slowed the investigation of motor ability constructs. Subsequently, it was considered important to assess individual motor ability in order to recognise and understand individual motor development or motor impairment. With uncertainty surrounding task generality or specificity, the ‘motor ability’ phrase has resulted in the use of terms such as motor proficiency, motor skill or motor performance. As the new phrases became popular, motor ability issues were gradually blurred, and investigations into GMA decreased. With the research focus then tending to examine specific aspects of motor ability, several test instruments were developed and widely accepted. Such instruments include the Bruininks-Oseretsky Test of Motor Proficiency (Bruininks, 1978), Movement Assessment Battery for Children – Movement ABC (Henderson & Sugden, 1992), Test of Gross Motor Development (Ulrich, 1985, 2000) and the McCarron Assessment of Neuromuscular Development - MAND (McCarron, 1982) (see APPENDIX A on the CD for a summary of the motor ability test batteries). Although those tests did not clearly define GMA, they still measured individual GMA. Thus, Burton and Rodgerson (2001) revisited the issue of motor ability and supported the GMA concept by proposing a new movement taxonomy. This new taxonomy highlights the need for further investigation on the underlying construct of motor ability and GMA. 31 2.5. HUMAN MOVEMENT TAXONOMY Motor ability tests have been developed over the last 90-100 years for different purposes and age groups. Several developed taxonomies pertaining to movement skill assessment largely draw on one another. As the study of GMA and human movement developed and expanded the discipline areas, knowledge domains as well as taxonomies have also been transformed. Guilford (1958) pioneered taxonomy in motor ability and human movement. He proposed a two-dimensional system of motor abilities that classified ability on the basis of body parts involved in the movement (Table 1, APPENDIX B on the CD). These classifications are based on three types of test items; tests of physical fitness, apparatus-tests and printed tests, and are supported by studies using factor analysis. The two-dimensional classification system has several implications as other abilities could remain undiscovered. This ability classification was specific to anatomical aspects and no categorisation had been allocated for combined-factors such as power and agility (Guilford, 1958). Therefore, Fleishman (1964) developed a classification system based on experimental confirmation by using factor analysis (Table 2, APPENDIX B on the CD) to identify nine physical proficiency abilities (Fleishman, 1964) and 11 psychomotor abilities (Fleishman, 1966). These classifications are widely adopted in studies of motor ability and the psychomotor domain (Burton & Miller, 1998). Then, Clarke (1967) generated a classification system pertaining to the psychomotor domain (Figure 1, APPENDIX B on the CD). She set out to categorise components of GMA and demonstrate their roles in motor fitness and physical fitness. This classification system showed that the same test item(s) sometimes could be used to measure individual GMA, motor fitness and physical fitness (Clarke, 1967). Due to the need for a comprehensive taxonomy from different areas of research, Harrow (1972) developed a taxonomy of the psychomotor domain which included six main levels in the taxonomy: Reflex Movements, Basic-Fundamental Movements, Perceptual Abilities, Physical Abilities, Skilled Movements and Non-Discursive Communication (Table 3, APPENDIX B on the CD). The physical abilities that were highly related to motor abilities were divided further into sub-categories of endurance, flexibility, strength and agility. Harrow (1972) maintained that, if physical abilities were not adequately developed, the achievement of highly skilled movement could be limited. Others agreed that motor ability achievement would limit movement or define potential for success in a particular activity 32 (Hensley & East, 1989; Schmidt & Lee, 1999). Baumgartner and Jackson (1975, 1991) included another three additional factors to the commonly used physical abilities noted above. These were power, balance and basic movement patterns; that involve sprinting, jumping and throwing (Table 4, APPENDIX B on the CD). In these taxonomies, the power, balance and basic movement patterns mostly focused on the individual. As task and environment influence movement, Knapp (1963) developed a classification of skills based along a continuum of closed to open skills. Based on this continuum, Gentile (1987) classified movement tasks into 16 levels according to how they were influenced by variation in the environment and object manipulation (Table 5, APPENDIX B on the CD). In 1998, Burton and Miller (1998) introduced a taxonomy of movement skills classified into six levels, namely: movement skill foundations, motor abilities, early movement milestones, fundamental movement skills, specialised movement skills and functional movement skills (Figure 2, APPENDIX B on the CD). In the taxonomy of movement skills, the movement foundations influence motor abilities. However, because tests of motor abilities do not directly evaluate movement skills, motor abilities are isolated from the sequence of true movement skills and assessed independently (Burton & Miller, 1998). This classification also excluded motor ability from any developmental levels of movement skills on the basis that motor ability evaluated movement competency. Burton and Rodgerson (2001) revised this taxonomy of movement skills and GMA (Figure 3, APPENDIX B on the CD) into four primary levels – movement skills, movement skill sets, movement skill foundations and GMA. In this taxonomy, motor ability was recognised as a movement skill foundation. Thus, assessment of movement skill foundations would identify factors that might limit or facilitate the functional outcome of a particular movement skill. The existence of any new taxonomy of movement skills and GMA demonstrates the need to clarify further the knowledge domain related to motor ability and GMA. 2.6. FACTORS UNDERLYING MOTOR ABILITY Historically, Spearman (1904) investigated children’s performances on academic tests and concluded that there was one general intelligence factor called ‘g’ which underlies performance on all sub-tests. Inspired by Spearman’s study, Garfield (1924) investigated motor abilities that underlie human motor performance. Larson (1941) sought to identify common characteristics of the various tests in order to develop a motor ability test for college men. In the first of two studies to develop the test, four motor ability factors were 33 identified from 33 test items. The four factors were dynamic strength, static dynamometric strength, gross body coordination and abdominal strength. The second study analysed dynamic strength with other motor ability tests. Factor analysis extracted four motor ability factors: gross body coordination and agility, dynamic strength, motor educability and motor explosiveness. Based on these findings, Larson (1941) created an Indoor Test Battery and an Outdoor Test Battery. The Indoor test items were dodging run, bar snap, chinning, dipping and vertical jump. A baseball distance throw, chinning, bar snap and vertical jump were the items in the Outdoor test battery. A series of factor analysis studies (Fleishman, 1954, 1956, 1957, 1958b) were conducted to investigate basic abilities and motor skills. Fleishman (1964) identified six physical abilities and 10 perceptual-motor abilities. The physical abilities included explosive strength, extent (flexion and extension) flexibility, dynamic flexibility, gross body equilibrium, balance with visual cues and speed of limb movement. The perceptual-motor abilities were control precision, multi-limb coordination, response orientation, reaction time, speed of arm movement, rate control, manual dexterity, finger dexterity, arm-hand steadiness, wrist-finger speed and aiming. After identifying physical and perceptual-motor ability factors, a test battery was developed. Fleishman (1964) recommended a battery of Basic Fitness Tests classified by the factors they measured. The 10 test items included extent flexibility, dynamic flexibility, shuttle run, softball throw, handgrips, pull-ups, leg lifts, cable jump, balance and 600-yard run/walk. The tests were claimed to measure: extent and dynamic flexibility; explosive, static, dynamic and trunk strength; coordination, equilibrium and stamina. Previous factor analysis studies acknowledged nine underlying factors of physical qualities and 18 underlying factors of motor educability (Carpenter, 1941; Gates & Sheffield, 1940; McCloy, 1934a; McCloy & Young, 1954). They were categorised as either orthogonal or oblique factors (see Table 3). Oblique factors provided strong confirmation that second-order factor analysis was needed to better explain motor ability and GMA (McCloy & Young, 1954). In addition, several studies focused more on one element of motor ability such as coordination (Cumbee, 1954; Cumbee, Meyer & Peterson, 1957), flexibility (Harris, 1969), muscular strength (Kollias, Hatzitaki, Papaiakovou & Giatsis, 2001); or related areas such as physical fitness (Baumgartner & Zuidema, 1972; Zuidema & Baumgartner, 1974) with an emphasis on measuring individual physical fitness rather than motor ability (Fleishman, 1964). As definitions of motor coordination were diverse, Cumbee (1954) investigated 21 motor coordination variables among first year college women to determine what they actually 34 measured. Factor analysis with oblique rotation extracted eight factors. The factors found to underlie motor coordination were balancing objects, tempo, two-handed agility, speed of change of arm and hands, coordination, body balance and two unnamed factors. Cumbee (1954) concluded that previous motor coordination test items and motor proficiency or sports skills, cluster together a number of motor abilities. Cumbee, Meyer and Peterson (1957) did a follow-up study on motor coordination ability among third and fourth grade girls. Nine factors were extracted using factor analysis with oblique rotation, and several were similar to those in the previous study. However, some different factors also were found to underlie motor coordination ability. The factors identified that were similar to those in the earlier study were: balancing objects, speed of change of direction of the arms and hands, and body balance. Total body quick change of direction, vertical body quick change of direction and four other unnamed factors were also identified. Comparative analyses on results from both studies by Cumbee (1954) and Cumbee et al. (1957) showed that the inter-correlation matrices among elementary samples were more specific when compared with those of the earlier college sample. Therefore, Cumbee et al. (1957) suggested that a different definition of motor coordination for different age levels should be considered. 35 Table 3. Categorised Factors Underlying Physical Qualities and Motor Educability. Factors Group of Factors Type of factor Physical Muscular strength Orthogonal Qualities Speed of muscular contraction Orthogonal Dynamic energy Probably oblique Ability to change direction Probably oblique Muscular endurance Orthogonal Cardio-respiratory endurance Orthogonal Agility Probably oblique Dead weight Orthogonal Flexibility Probably orthogonal Motor Insight into nature of skill Probably orthogonal Educability Depth perception Probably orthogonal General-kinaesthetic sensitivity and control Orthogonal Balance Eyes and balance in movement in general Eyes and balance in Orthogonal forward-and- backward movement Orthogonal Eyes and balance in sideward movement Orthogonal Vertical semicircular canals and balance Orthogonal Horizontal semicircular canals and balance Orthogonal Tension-giving reinforcement Probably oblique Kinaesthetic sensitivity and control Not reported Perceptual speed Probably orthogonal Ability to visualise spatial relationships Orthogonal Sensory-motor coordination I Orthogonal Sensory-motor coordination II Probably oblique Judgment concerning time, height, distance Orthogonal and direction Coordination for complex unitary movement Orthogonal or oblique Coordination for combination of movements Not reported Arm control Probably oblique Accuracy of direction Probably oblique Sensory rhythm Not reported 36 Table 3 continued. Timing Probably oblique Duration of time Probably oblique Insightful timing Probably oblique Motor rhythm Probably oblique Quick and adaptive decisions Not reported Aesthetic feelings Probably oblique From: McCloy, C. H. & Young, N. D. (1954). Tests and Measurements in Health and Physical Education. New York: Appleton-Century-Crofts Educational Division Meredith Corporation. In summary, research has found basic constructs underlying the test items measuring a specific motor skill but, due to the specificity of the research, it has not enabled an examination of GMA. This study included various motor skill measurements to examine their underlying constructs and explore the possibility of the GMA construct. 2.7. DISCRIMINATING ITEMS IN MOTOR ABILITY Several studies investigated test items which allocate individuals into different motor ability or performance groups by using discriminant analysis (Gabbett, Georgieff & Domrow, 2007; Rarick, Dobbins & Broadhead, 1976). Others have examined anthropometric and biomotor ability variables among adolescent females (Leone, Lariviere & Comtois, 2002), male athletes (Leone & Lariviere, 1998) and from different sports (Cagno et al., 2008; Cavala, Rojulj, Srhoj, Srhoj & Katic, 2008; Douda, Toubekis, Avloniti & Tokmakidis, 2008; Falk, Lidor, Lander & Lang, 2004; Lidor, Hershko, Bilkevitz, Arnon & Falk, 2007). Leone et al. (2002) examined young female athletes aged 12-17 years who participated in tennis, skating, swimming or volleyball. Findings from their first discriminant function analysis showed that most of the variability reflected differences in anthropometric and biomotor variables between figure skaters and other composite groups of athletes. The anthropometric measures showed that figure skaters obtained the lowest values when compared with other athletic groups. From the bio-motor measures, figure skaters obtained the best scores in burpees and trunk flexibility, but lowest in the push-up test. The flexibility test significantly discriminated between figure skaters and tennis players (p < .05). 37 The second level discriminant function analysis showed that the anthropometric measures also could differentiate between swimmers and volleyball players. Body mass, biceps brachii and calf girths, and height were the best discriminators of these groups. The volleyball players were taller and heavier than the swimmers, while the swimmers had larger bicep girths than volleyball players. From the bio-motor perspective, the swimmers revealed higher scores than volleyballers except for maximal aerobic power. However, the bio-motor measures were unable to discriminate swimmers from other groups of athletes. The authors concluded that anthropometric measures had greater potential to discriminate between female athletes from four different sports than did the bio-motor measures. Male participants from tennis, figure skating, cycling and gymnastics (Leone & Lariviere, 1998) demonstrated maximal aerobic power (MAP) and trunk flexibility discriminated between gymnasts and the other athletes. In contrast, MAP and muscular endurance (burpee test) best discriminated between cyclists and tennis players, although both groups recorded similar anthropometric dimensions. Gabbett et al. (2007) conducted a discriminant analysis on selected and non-selected junior volleyball players to a high level squad to determine the performance data that would discriminate between those selected and those not selected. The results of the study indicated that passing technique and serving technique, but not physiological or anthropometric data discriminated between successful and non-successful volleyball players. Cagno et al. (2008) investigated leaping ability and morphological characteristics in rhythmic gymnastics to determine the characteristics most useful for TI. Several factors emerged when comparing elite gymnasts with sub-elite gymnasts. The elite gymnasts were taller, had longer legs, more fat free mass and hopped higher than the sub-elite counterparts. Cavala et al. (2008) examined a range of morphological characteristics, basic motor abilities, and specific situational motor abilities in female handball players. They found that handball performance was determined by agility and explosiveness, and by integrating basic motor abilities of coordination/agility and all explosive strength types (throwing, running and jumping). Morphologically, greater muscle mass also was found to be important in handball. Douda et al. (2008) investigated anthropometric predictors of gymnastic performance. The elite gymnasts recorded greater aerobic capacity, flexibility, explosive strength and anaerobic capacity, but lower body mass and particular anthropometric characteristics than their sub-elite counterparts. These qualities appear to be important in gymnastics. 38 Lidor et al. (2007) examined a battery of physical and motor tests, and two serving skill tests were examined for their usefulness in the early detection and development of volleyball players. Results indicated that only one physical explosive power movement, the vertical jump with approach discriminated between starting and non-starting volleyball players. The other speed tests, agility run, explosive power tests, endurance test and serving skill tests, were not sensitive enough to distinguish between good and very good players. Finally, Falk et al. (2004) found that the players selected for the National water polo team already were skilled at swimming, handling the ball and game intelligence. Over the 2-year period the selected players improved their swimming and throwing-the-ball-for-distance than the non-selected players. These studies indicated that anthropometric and bio-motor measures can discriminate between athletes, and can serve as markers to help direct potential athletes into sports for which they are most suited. Knowing these characteristics would also help streamline the tests done during the TI mass screening phase. 2.8. MOTOR ABILITY STUDIES AMONG ADOLESCENTS Generally, TI assesses motor ability during adolescence when body size changes and motor performances significantly impact on proficiency in sports skills (Beunen et al., 1988). While the variation in growth spurts and hormonal changes presents interpretative challenges, individuals often select a main sporting direction at these ages. Hence, evidence based guidance for choosing where maximum success might be achieved is timely and effective. Espenschade (1940) conducted a longitudinal study of the relationship between motor performance and age, gender, physical growth and maturity among 13-15 year old adolescents. The test items were: distance throw (arm and shoulder girdle coordination); target throw (hand-eye, arm-eye coordination); standing long jump, and jump-and-reach (jumping or leg strength and flexibility); Brace test (body coordination, agility and control); and the 50 yard (45.7 m) dash and dodging run (speed of legs). When comparing these motor test scores with other indicators of motor performance, consistent agreement in differentiating between superior and inferior subjects were reported. Espenschade (1940) also found the mean performance of all boys to increase steadily in all events with age but the girls were different in some events. The girls’ mean performances improved but reached a maximum level around 14 years and decreased gradually thereafter. A gradual decline was evident in the dash and long jump tests. However, the girls’ scores in 39 distance throws and Brace tests were fairly stable, and increased in the jump-and-reach scores. Adolescent girls reached their maximum performances in certain events around 14 years, whereas adolescent boys continued to improve their motor performances through to 17 years old. Also, gender differences were noted at all ages and the older subjects demonstrated bigger performance discrepancies than the younger children. Later, a review of motor development changes from childhood to adolescence in the USA showed similar trends in motor performance (Glassow & Kruse, 1960; Rarick & Smoll, 1967). This suggested that human motor development shows stability across age and gender, with a few variations because of different cohort variations during childhood and adolescence. Beunen et al. (1988) carried out a 5 year, longitudinal growth and performance study of Belgian adolescent boys. They obtained descriptive data with which to compare the distance and velocity curves of other Belgian data, and to investigate adolescents’ changes in somatic and motor characteristics based on chronological age. The study reported anthropometric measures and motor ability tests which emphasised strength. The motor ability test items (and factors identified) were bent-arm hang (functional strength), arm pull (static strength), vertical jump (explosive strength), leg lifts (trunk strength), sit-and-reach (flexibility), 50m shuttle run (running speed), plate tapping (speed of limb movement), stick balance (eyehand coordination) and one minute step test (pulse recovery). In the chronological age-based distance and velocity curves, static and explosive strength (arm pull and vertical jump) closely followed the reference group pattern, and increased linearly; with the largest increase occurring from 14.5-17 years old. However, static strength continued to increase while explosive strength reached a plateau at 17 years. Functional strength also increased from 12.5 to 16 years, while trunk strength increased in a limited fashion at discrete ages; namely, 14.0, 14.5 and 17.5 years. Speed of limb movement also increased linearly between 12.5 and 16.5 years of age, and plateaued thereafter. Running speed performance improved from 12.5 to 17.5 years, while flexibility increased from 13.0 to 17.5 years. Running velocities and speed of limb movements declined steadily after 13-14 years of age but the velocity curves of strength and flexibility remained stable. Proctor & Ruhling (1981) studied adolescent female athletes and non-athletes to determine the similarities in seven selected motor characteristics. Subjects participated in basketball and gymnastics, and non-athletes acted as controls. The seven selected motor tests were arm circling, balance test, basketball wall pass, dash, leg rise, stand and squat, and the standing 40 long jump. The stepwise discriminant analysis showed that only dash, stand and squat, and balance tests discriminated between the three groups. Based on the constants and coefficients from those three variables, Proctor and Ruhling (1981) developed equations to predict individual future group allocation. Also, a cross-cultural study measured motor abilities between the two Baltic countries of Estonia and Lithuania by using EUROFIT tests (Jurimae & Volbekiene, 1998). Participants were 11-17 years old and selected from schools in every division of towns in each country. The EUROFIT motor ability test items were sit-and-reach, hand-grip strength, standing long jump, 10m x 5 m shuttle-run, plate tapping, bent-arm hang, sit-ups and 20m endurance shuttle-run. No significant differences were found in anthropometric measures between the Estonian and Lithuanian children. The Estonian boys and girls scored significantly higher in the 20m endurance shuttle-run than did Lithuanian children of similar age and gender, except for the 14-year old boys. Generally, Estonian children scored higher on hand-grip strength, 10 x 5m shuttle-run, sit-and-reach (among girls aged 12-15 years) and flamingo balance (girls). On the other hand, the Lithuanian boys scored higher in bent arm hang than Estonian boys of the same age. Jurimae and Volbekiene (1998) indicated that, despite the Estonian and Lithuanian children’s motor abilities being comparable with other European children, performances were influenced by environment factors. Environmental influences were observed in gender differences and it was suggested that such influences are vital prior to puberty (Jurimae & Volbekiene, 1998; Thomas & French, 1985). Several studies of anthropometric variables and developmental changes in motor abilities related to age have been conducted on boys (Cheng, 2001; Planinsec, 2001; Viru et al., 1998) and girls (Kim, French & Spurgeon, 1999; Little, Day & Steinke, 1997; Loko, Aule, Sikkut, Ereline & Viru, 2003; Viru et al., 1998; Volver & Selge, 1997; Volver, Viru & Viru, 2000). Anthropometric variables and improvement in motor abilities are associated with the periodical acceleration of changes in adolescence. In most cases, age periods have been used as an index for monitoring accelerated improvement in motor abilities. Other studies have employed maturational stages as a reference when assessing motor ability performance. Table 4 summarises different time periods in which peak rates of motor ability improvements were found among adolescents (Viru et al., 1998). It is difficult to interpret different rates of improvement in motor abilities according to age and gender, and large growth and development variations during adolescence, when selecting exceptional abilities among children in a TI program. It is a complex mission involving factors other than just motor ability. Fleishman (1957) suggested that motor ability 41 was, initially, a general trait that became more specific after practising the motor skills. As the goal of TI is to recognise talent or expertise, the latter phase is the one in which talent is domain specific. Table 4. Rate of Motor Ability Improvements. Motor Abilities Boys (age) Girls (age) Speed 7 – 8 and 14 - 15 years old 8 – 9 and 12 – 13 years old Explosive strength 7 – 9 and 13 – 16 years old 6 – 8 and 11 – 12 years old Muscle strength 14 – 16 years old 12 – 13 years old Aerobic endurance 11 – 15 years old 11 – 13 years old From Viru et al. (1998) In summary, motor ability and talent in sport are important concepts that portray a human motor ability continuum. The given definitions of ‘raw talent’ or giftedness, and ability, show that both elements are similar under the same continuum, and represent an individual, internal and innate capacity. Abilities are general traits which underlie capabilities that support many skills (Schmidt & Lee, 1999) whereas being expert refers to an exceptionally high skill level that is relatively domain specific (Howe et al., 1998). Researchers now use the concept of raw talent extensively to predict exceptional abilities (Howe et al., 1998) and to develop expertise (Ericsson & Lehmann, 1996). Generally, TI programs use mass, sport specific and talent development screening; and motor ability affects performance in these processes. Thus, thoroughly assessing motor ability would assist in identifying potential athletic talent to maximise opportunities for success via appropriate training in sports for which they are best suited. The present study set out to do this within a Malaysian context. Further investigation of inter-relationships, factors across gender and age, accuracy of standard tests with other TI tests and motor ability instruments, should confirm previous evidence of the value of basic level TI assessments. Identifying potentially talented athletes via scientifically based motor ability tests could possibly affirm the existence of GMA. 42 CHAPTER 3 METHODS AND PROCEDURES Approval for the study was granted by The University of Western Australia Human Rights and Ethics Committee. Prior to any testing, procedures followed three distinct phases over a six month time period. The first phase was selection of motor skill instruments. 3.1. INSTRUMENTS. Three motor skill instruments in the current research are summarised below. i. McCarron Assessment of Neuromuscular Development Test (MAND) (McCarron, 1982) - was selected because, unlike other standardised motor ability tests, it can measure a range of ages from three years old to young adults. Also, age based test norms are provided for grip strength and jumping items, and norms according to gender and age are available which start at the 14 year old group. Other motor ability tests generally focus on children and young adolescents. For example, the Movement Assessment Battery for Children can be used with children aged 4-12 years old (Henderson & Sugden, 1992). The Test of Gross Motor Development is for evaluation of gross motor skill development of children aged 310 years (Ulrich, 1985, 2000). Finally, the Bruininks-Oseretsky Test of Motor Proficiency (Bruininks, 1978) measures gross and fine motor abilities among 4-14 year old children, but does not include separate norms for gender. However, it acknowledges that gender differences should be considered. The MAND consists of five fine motor tasks and five gross motor tasks. The fine motor tasks are beads-in-box, beads-in-rod, finger tapping, nutand-bolt, and rod slide. The gross motor tasks include hand strength, finger-nose-finger movements, jumping, heel-toe-tandem-walking and standing-on-one-foot. ii. Australian Institute of Sport Talent Identification Test (AIS) (Australian Sports Commission, 1998) – selected because the Australian Sports Commission (1998) found that the 40m sprint measures a speed component, the basketball throw measures upper body strength, the vertical jump measures ability to spring in a vertical direction, and the multistage fitness test measures aerobic fitness. The tests included in this battery are height, weight, 40m sprint, vertical jump test, basketball throw and multistage fitness test. 43 iii. Balance and Movement Coordination (BMC) Test – was developed by the author for this study because the Movement Skill Foundations Checklist by Burton and Miller (1998), and considerable research, recommended including two components of motor ability, namely, balance and movement coordination. (see APPENDIX C on the CD for additional detail for the selection of the motor skills for the BMC). These were measured via fieldbased tests. There were three motor skills of balance and six motor skills of movement coordination making up the BMC. The balance skills were one-foot-balance-with-eyes-open, one-foot balance-with-eyes-closed and dynamic balance. For movement coordination, the motor skills were shuttle-run-without-object, shuttle-run-with-object, hopping-in-square, hopping speed, zigzag run and quadrant jump. The BMC motor skills have good test-retest reliability but, as the BMC was developed for this study, details of the reliability analysis are in Chapter 5. The motor skills included in the BMC were based on a task analysis of the requirements of the activity. The justification for including tasks in order to test for a particular ability is provided below. • Balance ability Static balance was assessed via a one-foot-balance-with-eyes-open and a one-foot-balancewith-eyes-closed. Balancing on one foot is commonly used to measure static balance (Bass, 1939; Burton & Davis, 1992; Johnson & Nelson, 1986; Largo, Fischer & Calflisch, 2002; McCarron, 1982). To avoid ceiling effects among participants, difficulty was increased by subjects holding a rod overhead with outstretched arms to hold the balance for a 60s maximum time on each foot, with eyes open and closed. Dynamic balance has been tested using sidesteps with the legs together while jumping sideways (Largo et al., 2002). In this study, participants jumped sideways continuously for 10s. • Movement coordination ability Six motor skills were selected to measure movement coordination ability: shuttle-runwithout-object, shuttle-run-with-object, hopping-in-square, hopping speed, zigzag run and quadrant jump. Generally, running has been considered an adequate test of gross body coordination (Pyke, 1986; Williams, 1983). However, task analyses on the shuttle-runwithout-object, shuttle-run-with-object and zigzag run, have indicated that these tasks also involved propulsion, running action and ability to change directions, while moving and executing the manoeuvres continuously. Propulsion requires a maximum force to initiate forward motion. As coordination ability governs and organises movements, the adjustment of timing and muscular control (Broer, 1973) fine tunes the organised movement for efficient performances based on the task demands. The adjusted elements of reaching objects in a shuttle run (amplitude and displacement), changing direction when performing a zigzag 44 run and quadrant jump tasks (ability to adjust movement based on context and specific task demands) requires specific muscular control of force, speed, direction and range of movements. In addition, the ability to hop continuously in a stationary position (hopping-insquare) or moving forward (hopping speed) requires strength, coordination, balance and rhythm. The coordination factor refers to the ability to perform simple movements without unnecessary tension and in proper sequence (Broer, 1973) to effect a smooth complex movement (Fleishman, 1964). Hence, the six motor skills chosen were considered sufficiently complex to elicit varying degrees of coordination in this study. 3.2. TRANSLATION OF TEST INSTRUMENTS INTO MALAY. As the subjects were Malaysian, and Bahasa Malaysia (Malay language) was their first language, instructions and descriptions of all instruments needed to be translated into Malay. Thus, the second phase involved translating the instructions and procedures of those tests for use in Malaysia, and a pilot evaluation of the translations. Initially, the translation of the MAND, AIS and BMC tests involved preparing a preliminary Malay version by two bilingual individuals and the author. This provided an initial Malay version of the instruments, which focused on presenting the clarity and quality of the Malay language into a relatively simple format, compatible with the education levels of the proposed subjects. These initial translations then were scrutinised further by two bilingual translators (Malaysian postgraduate students who studied at UWA and taught English as a second language at university level in Malaysia) and the author, and modifications were made to improve the clarity of the test instruments. This was a lengthy process and, approximately 3 weeks after the first meeting, a second meeting was held to discuss, evaluate and reach agreement on the Malay language terminology selected by the two translators from a language perspective; and the author and one Malaysian sports scientist as content experts. In the final part of the translation phase, the experimental version of the test instruments was pre-tested by two Malaysian high-school students (1 x 13 year old girl; and 1 x 14 year old boy) and three Malaysian college-students (mean age of 18.3 years). Malay was their first language, and they read and demonstrated the Malay language versions of the three motor ability test batteries. The author and a Malaysian sports scientist assessed their movements while they performed the tests, and monitored the parallel movements via the Malay instructions for the test instruments. Comments and suggestions from the students were taken into account when fine-tuning the next version. Each pilot test was conducted individually to prevent any subject copying another student’s interpretations of the language 45 when following the instructions. This fine tuning stage took 3 weeks to finish as the participants performed the testing over weekends and the researchers re-drafted the instructions during the week. During the developmental phase, participants also were encouraged to question anything that was unclear about the instructions and test items. Subsequently, they provided some minor changes on task instructions and test items for the final Malay version of the three motor ability test batteries. The author and Malaysian sport scientist had a final discussion regarding the suitability and relevance of the final instructions. Then, the instruments were cleared to use for data collection (see APPENDIX D on the CD). This whole process required more than 6 months of full-time development and fine-tuning. The third phase of the investigation involved accessing permission to proceed from the District and State Departments of Education, the Malaysian Ministry of Education; and then having actual schools and students agree to participate (see APPENDIX E on the CD for letters of permission). An attempt at stratified sampling was made initially but this was hampered by school principals’/teachers’ perceptions of interruption to student class time and use of sporting facilities. Hence, convenience sampling was used. 3.3. PARTICIPANTS. Three hundred and thirty students (165 boys and 165 girls) aged 12-15 years were recruited from two Malaysian high schools (see Table 5). The mean age for girls was 13.4 ± .99 years and the mean age for boys was 13.1 ± .98 years. Facilities were made available for the indoor and field tests over the four months of time needed for actual data collection. Table 5. Numbers and Percentages of Participants in the Research. Number of Participants Age (in years) Boys Girls Total % 12 55 37 92 27.9 13 53 54 107 32.4 14 41 49 90 27.3 15 16 25 41 12.4 TOTAL 165 165 330 100 46 3.4. ADMINISTRATION OF THE TESTS The participants were performance tested on the AIS, MAND and BMC motor skill instruments. A full description of these instruments is in APPENDIX F on the CD. The AIS instrument was administered to the adolescents following the methods outlined by the Australian Sports Commission (1998). The MAND was administered using the methods outlined by McCarron (1982). The BMC instrument was specifically designed for the current research and included motor skills focusing on movement coordination and balance (see APPENDIX F on the CD). A pilot study investigated the test-retest reliability of the BMC, MAND and AIS tests. Thirty-three subjects aged 13 years (20 boys, 13 girls) attended two test-retest sessions. These took place separately during two scheduled physical education lessons in the same week, and two days apart. Identical procedures were followed at both sessions. During both counterbalanced testing trials, instructions were offered verbally because students were keen to perform the tests rather than increase time by reading the instructions. The means, standard deviations and reliability scores for each test item are presented in Chapter 5. The first testing session was conducted indoors and participants were measured individually on the MAND motor skills in counterbalanced order. Then, in pairs, they moved from station-to-station for height and weight measures, one-foot-balance-with-eyes-closed and one-foot-balance-with-eyes-open (BMC test), and vertical jump (AIS test), alternately. For the second session, groups of eight participants performed the other motor skills of the AIS and BMC in a counterbalanced sequence. The participants had adequate rest between each test while waiting their turn. The sessions were conducted on the school field and subjects wore suitable physical education clothing (tracksuit, t-shirt, rubber-soled shoes). 3.5. DATA ANALYSIS Several stages of data reduction and analysis were then performed. i. Initially the data were screened for normality. Where there were issues regarding some of the variables they were transformed and the analyses run again. In all cases the analyses with corrected data the resuls were the same as that found for the uncorrected data. Thus, the results of the analyses with uncorrected data are presented. 47 ii. The MAND and the NDI - from the raw scores of participants’ fine and gross motor tasks, a scaled score was derived using age-appropriate norm tables provided in the MAND manual (McCarron, 1982). The Neuromuscular Development Index (NDI) was obtained by summing the scaled scores of the fine and gross motor averages, and converting the values using the tables provided (see APPENDIX G on the CD). The NDI was based on a distribution with a mean score of 100 and standard deviation of 15. The Neuromuscular Development Index (NDI) score determined participants’ levels of fine and gross motor skills. Descriptive information was obtained for the NDI. iii. Reliability of The MAND, AIS and BMC - The MAND, AIS and BMC motor skill instruments all underwent test-retest reliability procedures prior to formal testing. iv. Factor analyses were applied to determine the motor abilities underlying each of the MAND, AIS and BMC motor skill test batteries. Specifically a Principal Components Analysis (PCA) using the orthogonal (VARIMAX) rotation method was undertaken to reveal the underlying motor abilities. To remove the possible confounding effect of chronological age and gender differences, all the motor skill raw scores of the MAND, AIS and BMC were standardised separately for each gender by age-group classification. They were then transformed into T-scores based on means and standard deviations, for each gender and age group, and used in the subsequent analyses. Following an initial examination of the motor abilities underlying the MAND, AIS and BMC; a test for a ‘g’ in motor ability was undertaken via a factor analysis which proceeded in two stages. A first-order analysis was performed to determine the components underlying the combined AIS+BMC motor skills set and was followed by a higher-order factor analysis of the first-order components to test for ‘g’. A PCA analysis with oblique (PROMAX) rotation method (Rummel, 1970) was applied to reveal the underlying AIS+BMC components, and a higher-order factor analysis was performed on these components. The PROMAX oblique rotation method was used as this allowed factors to be correlated (Bohman, Heger, Smith, Barker & He, 1995) and was appropriate for second-order (Thurstone, 1947) or higher-order (Rummel, 1970) factor analysis. v. Descriptive statistics of the MAND, AIS, and BMC were then generated to provide normative information for future use in Malaysia. The raw scores of the MAND, AIS and BMC were utilised in these analyses. Additionally, a series of ANOVAs also were conducted to examine for age and gender effects. In total, there were 11 48 separate analyses and a Bonferroni correction was applied to the significance value of .05. The resulting p value used was .005. Effect sizes and Confidence Intervals were also calculated to clarify the meaningfulness of any significant results. vi. Finally, stepwise discriminant function analyses were used to identify the motor skills that reliably categorised the participants into either one of three motor coordination groups (i.e., Poor, Normal or High) based on their MAND scores or motor ability groups (i.e., Low, Normal or High) based on their motoric ‘g’ scores. Although it might not be strictly correct to use the 13 motor skills to create the ‘g’ scores, and then use the same skills to find the best sub-set of motor skills to reliably discriminate the 3 motor ability groups derived from these ‘g’ scores, this was done to see if a framework grounded in sport (i.e., the AIS+BMC) would provide better separation than one grounded in disability (i.e., the MAND). To remove any confounding effect of chronological age and gender differences, all the motor skill raw scores of the AIS and BMC were standardised separately for each gender-byage-group classification. They were then transformed into T-scores based on means and standard deviations, for each gender and age group and used in the discriminant analysis. The discriminant function analysis was conducted on all participants only due to insufficient numbers in the low motor coordination/ability groups for the boys. The statistical methodology employed was to derive the discriminant function via stepwise estimation. This approach reveals the best set of motor skills that can discriminate between the three groups. Then, an examination of the discriminant functions was made to note any motor skills of importance that, due to collinearity issues, were not present in the stepwise findings. The fit of the discriminant analysis was then assessed via jackknife classification using prior probabilities to account for the unequal sizes of the groups. The jackknife classification procedure was employed because the sample was unable to be split to allow for cross validation of the discriminant findings. This procedure estimates the discriminant model by leaving out one observation and then predicting that case with the estimated model. As this is done in turn for each observation, that observation never influences the discriminant model that predicts its classification (Hair et al., 1998). So, jackknifed classification gives a more realistic estimate of predictors and can separate the groups (Tabachnick & Fidell, 2007). Finally, the adolescents who were misclassified were examined to understand the nature of these individuals. For the misclassification examination, the standard predicted membership was based on the standard classification procedure, not the jackknife procedure. Thus, the misclassified groups’ n may differ from that used for the jackknife classification. 49 Factor analyses and discriminant function analyses are highly sensitive to outliers and missing data (Coakes & Steed, 1997; Tabachnick & Fidell, 1989). Additionally, standardising scores is essential if variables are measured on different scales (Field, 2000). Cases with standardised scores in excess of +3.00 standard deviations are potential outliers (Tabachnick & Fidell, 1989) and, usually, they are deleted. As this study sought to identify talented participants in which outlier data are important, data that exceeded +3.00 standard deviations were retained. All data were analysed using SPSS software 12.00 (SPSS Inc, 2004). As the description of results will be presented in chapters 4, 5 and 6, a summary of the statistical analyses is described in Table 6. 50 Table 6. Motor Skills, Scoring Method & Statistical Analyses from Chapters 4-6. Score and Score and Statistical Analysis Test Items Statistical Analysis MAND Bead in box Used raw Bead in rod obtain the Finger tapping score and for ANOVA Factor Analysis, and Nut and bolt analyses in Chapter 5 score to Used standardised T- percentile scores for First-Order Discriminant Function Analyses Rod slide Hand strength Finger-nose-finger movements Jumping Heel-toe tandem walking Standing on one-foot Note. The NDI was obtained by summing the scaled scores of each item and converting the values by using the tables provided in the manual. AIS BMC Height Used raw score to Used standardised T- Weight obtain the 40 m sprint score and for ANOVA Second Order Factor Vertical jump test analyses in Chapter 5 percentile scores for First and Analyses, and Basketball throw Discriminant Function Multistage fitness test Analyses One-foot balance with eyes open, One-foot balance with eyes closed Dynamic balance Shuttle run without object Shuttle run with object Hopping-in-square Hopping speed Zigzag run Quadrant jump Note. The ‘g’ score was obtained for each participant by deriving individual factor scores from the higher-order factor analysis testing a motoric ‘g’. 51 CHAPTER 4 FACTOR ANALYSES OF THE MOTOR SKILL INSTRUMENTS This chapter discusses the underlying constructs of the motor skill test batteries used in the study; and whether statistical approaches, such as higher order factor analysis, can provide evidence to support the concept of GMA, and if this is gender specific. Section A examines the factor structure of the motor skill tests. Burton and Miller (1998) contended that motor skill instruments must suitable for the population being studied and measure what the author purports it to measure. This is particularly pertinent to the current Malaysian research study as both the MAND (McCarron, 1982) and the Australian Institute of Sport Talent Identification Instrument (Australian Sports Commission, 1978) tests were developed with non-Asian populations. Also, the MAND (McCarron, 1982) was specifically developed as a diagnostic tool for neuromuscular difficulties that may indicate broader problems such as mental retardation and neurological dysfunction. However, in this study, the MAND served to help categorise the adolescents into three levels of basic motor skill and coordination for analysis purposes. McCarron (1982) provided details of two factor structures. The first was derived from a disabled population and supported a 2-factor fine and gross motor skill model. The second was derived from a normal population and resulted in a 4-factor model. The four motor ability components found were persistent control (rod slide and finger-nosefinger movement), muscle power (finger tapping, hand strength, and jumping), kinaesthetic integration (beads-in-box, heel-toe-tandem-walking, and standing-on-one-foot), and bimanual dexterity (beads-on-rod, and nut-and-bolt). However, subjects came from the USA and the two factor structures needed testing for their relevance with Malaysian adolescents. The AIS instrument identified four motor ability components that were important for identifying athletic talent in Australia. It consists of four motor skills that individually tap into each of speed, vertical jumping, upper body strength and aerobic fitness. This is an efficient way of measuring several motor abilities but, whether this model of motor abilities holds up outside an Australian context (i.e., Malaysian adolescents) remains to be seen. In contrast to the AIS instrument, the BMC is a motor skill instrument specifically developed by the author to measure motor ability components not assessed by the AIS instrument. The BMC assesses coordination and balance, two items of Burton’s (1993) 52 movement skills foundation checklist (Burton & Miller, 1998). These two movement skill foundations are essential to fundamental movement and an exhaustive library search was undertaken focusing on motor skills that assessed either balance or movement coordination. For each motor skill uncovered, a task analysis of that skill was then undertaken to ascertain whether that skill reflected fundamental movement (i.e., balance, running, jumping and hopping) with additional action (i.e., static, in-motion or change direction). This search uncovered nine motor skills for inclusion in the BMC that assessed movement coordination (i.e., the shuttle-run-without-object, shuttle-run-with-object, hopping-in-square, hopping speed, zigzag run and quadrant jump); and three motor skills that assessed balance (i.e., the one-foot-balance-with-eyes-open, one-foot-balance-with-eyes-closed and dynamic balance). Factor analysis was anticipated to support the existence of these two motor abilities. Section B examines the concept of GMA. Burton and Miller (1998) noted that, in order to assess motor skills adequately, at least two motor skill instruments that assess unique motor skills are necessary. Given that the current research was focused on finding motor skills relevant in helping identify athletic talent of Malaysian adolescents, the AIS and BMC motor skill instruments were combined to form the AIS+BMC instrument. This met Burton and Miller’s (1998) recommendation and also provided more motor skills than either the AIS or BMC alone, could provide a better opportunity to examine the existence of a ‘g’ in motor ability. The MAND was not included in these analyses as the motor skills assessed by the MAND were more suited to a basic level recognition of individual motor problems. However, the AIS and BMC are made up of motor skills that, at face value, appear to provide a wider range of motor skills more pertinent to sport. There are several approaches that can be used to test for the existence of GMA (Burton & Richardson, 2001). The approach used here was higher order factor analysis (Rummel, 1970). Given the exploratory nature of these analyses, no formal hypotheses were made on the motor abilities arising from such a pairing. However, from the first-order factor analysis of the AIS+BMC, the underlying factors or motor abilities were subjected to a second order factor analysis to test for a ‘g’ in motor ability. SECTION A - FACTORS UNDERLYING THE MAND, AIS AND BMC 4.1. RESULTS Initially, the raw scores from the motor skill tests were transformed into z scores for each gender-by-age-group classification, then into T-scores to eliminate the effects of gender and age. A series of Principal Component Analyses (PCA) were performed separately on the 53 MAND, AIS and BMC instruments. An examination of the Kaiser-Myer-Olkin and Bartlett’s Test of Sphericity indices indicated that the data were appropriate for factor analysis (Field, 2000). Specifically, the MAND item interdependence was suggested by a significant Bartlett's test of sphericity of 197.043 (p < .001) with a Kaiser-Meyer-Olkin sampling adequacy statistic of .62. The AIS test reported a Bartlett's test of sphericity of 103.495 (p < .001) and a Kaiser-Meyer-Olkin sampling adequacy statistic of .64. For the BMC test, a Bartlett's test of sphericity of 978.979 (p < .001) and the Kaiser-Meyer-Olkin sampling adequacy statistic was .83 was found. While KMO values higher than .90 are desirable, scores around .60 are tolerable. Decisions about the number of components to be extracted were based upon Kaiser’s criterion (eigenvalues > 1) and Cattell’s screen test. To ease interpretation of the pattern matrix, an orthogonal rotation method using the VARIMAX rotation was conducted on each motor skill battery (Coakes & Steed, 1997; Rummel, 1970). Results for each factor analysis consist of rotated factor loadings > .10. However, the factor interpretations were based on the variables with loadings of ≥ .40. This more conservative loading was chosen, given the sample size (N = 330) and number of variables being analysed in the smallest test battery (i.e., four in the AIS) (Hair, Anderson, Tatham & Black, 1998). 4.1.1. The MAND McCarron (1982) developed the MAND to assess fine and gross motor ability at a basic level. The instrument is primarily used to identify motor problems that underscore neurological dysfunction within individuals. McCarron (1982) provides details of a 2-factor psychometric model and a 4-factor psychometric model based upon the development work of the MAND. The 2-factor model consists of the fine and gross motor components derived by McCarron (1982) from a sample of motor challenged children. The second is a 4-factor model that McCarron (1982) reported for a sample of normal children aged 7 years (see APPENDIX H on the CD for the CFAs for these two factor structures). For the sample of Malaysian adolescents, a Principal Component Analysis (PCA) with VARIMAX rotation of the MAND’s 10 motor skills extracted three components. Results showed a modest 43.91% of the total variance was explained by these components. The eigenvalue, loadings greater than .10 and the intercorrelation matrix are presented in Table 7. Component One: The motor skills that loaded substantially were: heel-toe (.705), balance MAND (.639), finger-nose-finger (.587) and jumping (.518). 54 Component Two: This component had loadings on: beads-on-rod (.723), beads-in-box (.708) and nut-and-bolt (.596). Component Three: High loadings for this component were: grip strength (.766) and finger tapping (.689). Table 7. Correlations, Components and Loadings for the MAND for All Participants. Component 1 2 3 Eigenvalue 1.96 1.33 1.10 Motor Skill 1 2 3 4 5 6 7 8 9 10 1. Heel-toe - .23 .21 .22 .07 .02 .01 .12 .06 .14 .705 - .17 .18 .14 .09 .05 .05 .00 .08 .639 - .14 .15 -.02 .06 .14 .13 -.01 .587 - .12 .16 .07 .09 .21 .02 .518 .199 .157 - .31 .22 .17 .06 .11 .141 .723 .107 - .16 .12 -.07 -.04 - .06 .04 .02 - .03 .08 .229 - .17 .104 2. Balance MAND 3. Finger-nose-finger 4. Jumping 5. Beads on rod 6. Beads in box 7. Nut and bolt 8. Rod slide 9. Grip strength 10. Finger tapping -.132 .708 -.276 .596 .104 .340 .115 - Note. Loadings greater than .40 are in bold. 4.1.2. The AIS Instrument The Australian Sports Commission (1998) stated that the AIS test instrument assesses four different motor abilities - speed, ability to spring in a vertical direction, upper body strengthand aerobic fitness. Therefore, it was expected that this 4-factor solution would be revealed in the PCA. However, this was not the case. The exploratory factor analysis extracted one component that was comprised of all four motor skills, with a modest 42.9% of total variance being explained. The eigenvalue, loadings greater than .10 and the intercorrelation matrix are presented in Table 8. .766 .689 55 Table 8. Correlations, Component and Loadings for the AIS for All Participants. Component 1 Eigenvalue 1.72 Motor Skill 1 2 3 4 1. 40m sprint - .40 .27 .18 .754 - .22 .12 .701 - .21 .642 - .495 2. Multistage fitness test 3. Vertical jump 4. Basketball Note. Loadings greater than .40 are in bold. Component One: The loadings for the four motor skills are: 40m sprint (.754), multistage fitness test (.701), vertical jump (.642) and basketball throw (.495). 4.1.3. The BMC In the current research, an additional motor skill instrument was developed to assess movement skills not covered by the AIS. Specifically, nine motor skills were selected to assess two aspects of Burton and Miller’s (1998) movement skills foundation checklist. They are movement coordination (via the shuttle-run-without-object, shuttle-run-withobject, hopping-in-square, hopping speed, zigzag run and quadrant jump) and balance (via the one-foot-balance-with-eyes-open, one-foot-balance-with-eyes-closed and dynamic balance). It was expected that factor analysis would support the existence of these two motor abilities. However, the exploratory PCA revealed three rotated components from the nine motor skills of the BMC, with a modest 66.3% of total variance being explained. For eigenvalues, loadings > .10 and the correlation matrix, see Table 9. Component One: The motor skills that loaded substantially on this component were: shuttle run (.881), shuttle-run-with-object (.875), hopping speed (.781) and zigzag run (.713). Component Two: High loadings in this component were: the dynamic balance (.808), hopping-in-square (.763) and quadrant jump (.592). Component Three: This component had loadings on: one-foot-balance-with-eyes-open (.853) and one-foot-balance-with-eyes-closed (.728). 56 Table 9. Correlations, Components and Loadings for the BMC for All Participants. Components 1 2 3 Eigenvalue 3.75 1.17 1.04 .125 Motor Skill 1 2 3 4 5 6 7 8 9 1. Shuttle run - .81 .65 .57 .32 .26 .34 .18 .33 .881 .176 - .59 .55 .27 .23 .31 .15 .27 .875 .128 - .58 .31 .24 .29 .22 .27 .781 .182 .164 - .35 .31 .29 .17 .30 .713 .290 .131 - .43 .40 .18 .22 .173 .808 .115 - .24 .15 .17 .112 .763 - .15 .21 .259 .592 .113 - .33 .105 .853 .117 .728 2. Shuttle run with object 3. Hopping speed 4. Zigzag run 5. Dynamic balance 6. Hopping-in-square 7. Quadrant jump 8. One-foot balance with eyes open 9. One-foot balance with eyes closed - .255 Note. Loadings greater than .40 are in bold. 4.2. 4.2.1. DISCUSSION: FACTORS UNDERLYING THE MAND, AIS AND BMC The MAND The exploratory factor analysis on the MAND data identified three motor abilities explaining 43.9% of the total variance. Using a loading cut-off level of .40, nine of the MAND motor skill tests loaded positively on to one of the three identified motor abilities. This finding is at odds with the 2-factor and 4-factor models reported by McCarron (1982). The first motor ability consisted of 4 gross motor skills - heel-toe-tandem-walking, standingon-one-foot, finger-nose-finger movements, and jumping. Three of these tasks (i.e., heel-toetandem-walking, standing-on-one-foot, and jumping) encompass ‘the ability to maintain or control the centre of mass in relation to the base of support to prevent falls and complete desired movements’ (Westcott et al., 1997, p. 630). The jumping task purportedly measures power, but to perform this task well, individuals must also retain equilibrium throughout the jump (McCarron, 1982). While the strength component of the jump directly influences individual power (Fleishman, 1964), to perform this motor skill well requires optimal balance control in an upright posture (Kollmitzer et al., 2000). Therefore, the postural 57 control aspect of the jumping task may have influenced the strength of its relationship with the other motor skills in this factor. The motor skill of finger-nose-finger movements also loaded onto this factor. This is a measure of eye-hand coordination that requires an ability to focus attention while inhibiting extraneous movements. An ability to inhibit extraneous movements is also necessary for successful performance in the motor skills of heel-toetandem-walking and standing-on-one-foot. Being able to control extraneous movements in these three motor skills might explain why the measure of eye-hand coordination loaded onto this factor. Thus, given the importance of being able to control extraneous motor movements and being able to control one’s centre of mass, it was decided to label this motor ability ‘postural control’. The three motor skills making up component two consisted of the fine motor skills of beadson-rod, beads-in-box, and nut-and-bolt. These three motor skills require skill in well directed arm-hand movements to manipulate objects at speed (Fleishman, 1964; Hempel & Fleishman, 1955). The motor skills of beads-on-rod, and nut-and-bolt, require two-hand coordination to perform successfully. It should be noted that McCarron (1982) found these two fine motor skills loaded together to form a bi-manual dexterity factor in a factor analysis of the MAND in normal children. However, this research found the beads-in-box motor skill also loaded highly with beads-on-rod, and nut-and-bolt. This motor skill was like the other two in that it requires consistent movements of hand and forearm to move the beads into the box, and a degree of coordination to perform the task successfully. Finally, although not reaching the cut-off point for inclusion in a factor; the rod slide task, a slow activity, also loaded positively at .34 on component two. As a package then, the motor skills making up this factor all require well directed and controlled arm-hand movements (Kent, 1994). Thus, although slightly different from McCarron’s findings, this motor ability could also be called ‘bi-manual dexterity’. Component three consists of two motor skills; namely, grip strength and the fine motor skill of finger tapping. McCarron (1982) also found these two motor skills both loaded onto a factor (i.e., muscle power) in a factor analysis of the MAND in normal children. However, unlike McCarron’s findings (the motor skill- jumping- also loaded), only these two motor skills loaded onto component three in the current research. Both motor skills require rapid coordination of muscular movements, either via fast and continuous finger tapping, or through one explosive act of grip strength. Both motor skills also require control of muscle movements in sequence and displacement at speed. Attainment of both tasks indicates an individual’s ability to act in response to a rapid and precise movement (Kent, 1994). Given 58 that component three is similar to the muscle power factor reported by McCarron (1982) this component was similarly named, ‘muscle power’. The PCA analysis revealed three underlying motor abilities for the MAND - postural control, bi-manual dexterity and muscle power. Others also have found underlying constructs for the MAND. For instance, 8-12 year old Australian children exhibited three factors for the MAND that were similar to those reported in this study (Larkin and Rose,1998). They labelled their factors as kinaesthetic integration, manual dexterity and muscle strength. However, as noted before, McCarron (1982) identified a 2-factor model among working, mentally disabled adults (i.e., fine motor skill and gross motor skill), and a 4-factor model among normal children aged 7 years old (i.e., persistent control, muscle power, kinaesthetic integration and bi-manual dexterity). Thus, the MAND is a competent instrument when assessing motor skills at a basic level. But, when it comes to understanding what it is that the MAND is measuring from a more general perspective, this appears to change and depend upon the population under investigation. Earlier research acknowledged that different factor constructs will emerge from different age groups and different levels of motor difficulty (e.g., McCarron, 1982; Rarick, Dobbins & Broadhead, 1976). So, to understand what that instrument is assessing, relative to the population under investigation, Burton and Miller’s (1998) recommendation to examine the psychometric properties of an instrument appears warranted. Finally, the MANDs solution had a percentage of total variance explained below 50%. Tinsley and Tinsley (1987) have cautioned researchers when interpreting identified factor solutions having < 50% of the total variance explained, because such solutions are marginal. Thus, the 3 component solution found here for the MAND needs to be cross validated before one can be confident in its veracity. Therefore, caution is required when interpreting the present findings of the MAND. 4.2.2. The AIS Instrument The AIS instrument records information regarding basic anthropometric measures of height and weight; and motor skill performance. Specifically, the Australian Sports Commission (1998) identified four motor skills that assessed speed, ability to spring in a vertical direction, upper body strength and aerobic fitness. However, this structure was not found for the Malaysian adolescent sample. In the current research, the factor analysis demonstrated that one component explained approximately 43% of the total variance in the solution in contrast to that purported by the Australian Sports Commission (1998). An examination of the nature of this component was then undertaken. Anaerobic power is demonstrated in both 59 the 40m sprint and the multistage fitness tests because both require maximal rates of energy production with high intensity (Anshel, 1991; Bencke et al., 2002; Manning, DoolyManning & Perrin, 1988). Additionally, explosive power also is indicated via the basketball throw and the vertical jump because each activity requires one explosive act (Bencke et al., 2002; Kent, 1994; Manning et al., 1988). Considering the contribution of the elements of anaerobic power and explosive power being fundamental to this construct, and that ‘energy burst’ or ‘explosive act’ has been referred to as anaerobic power (Manning et al., 1988), this component was described as ‘explosive power’. A task analysis of the motor skills making up the AIS instrument indicated that each skill has similar performance requirements by the upper and lower limb power contributions to execute the tasks. According to Fleishman (1964), inefficient test batteries are those with too many tests on one factor, or none from one or more of the other factors identified. Within the context of the current research, if one just wanted to assess explosive power in Malaysian adolescents, having them complete four tests that measure explosive power may be inefficient. However, each motor skill of the AIS instrument assesses different aspects of explosive power and, consequently, each may be important when identifying athletic talent. Similarly, just focusing on one or two aspects of explosive power provides only part of the picture. Finally, there are two concerns regarding the PCA analysis of the AIS test. Firstly, these findings seem to suggest that the AIS instrument does not assess four separate motor abilities - only assessing one motor ability, that of explosive power. Therefore, as with the MAND, it may be necessary to evaluate the AIS instrument at each new setting. Secondly, as with the MAND, the AIS solution found here had < 50% of total variance explained. Thus, despite the intuitive appeal of the four motor skills measuring anaerobic power, caution is needed when interpreting the findings of the AIS analysis. 4.2.3. The BMC Test Nine motor skills were chosen to assess two motor ability components from the Burton and Miller (1998) fundamental movement skill foundations checklist - movement coordination and balance. The subsequent exploratory factor analysis revealed three motor abilities underlying the nine BMC motor skills and these explained 66% of the total variance in the solution. Four motor skills were extracted for the first component. These were shuttle run, shuttle-runwith-object, hopping speed and zigzag run. The loadings for the two shuttle run tasks were 60 above .80. These loadings are considered very high and, subsequently, these two motor skills became important in defining the nature of factor one (Hair et al., 1998). Hilsendager, Strow and Ackerman (1969) maintained that the shuttle and zigzag runs require agility, as both tasks involve rapid movement and change in the direction of movement. However, Hilsendager et al. (1969) also rejected the interaction of speed and strength in the agility component. Hopping at speed requires both strength and speed (Chelly & Denis, 2001) and an ability to maintain balance in a small base of support (Haywood, 1993a). A task analysis of the shuttle-run-with-object and the zigzag run showed that these tasks required additional movement through manipulating an object (i.e., shuttle-run-with-object) or completing a zigzag run from two different directions (i.e., the zigzag run). In other words, the participants were required to coordinate and integrate different movements into specific patterns peculiar to that motor skill. Barrow (1977) indicated that speed, balance, agility and kinaesthetic sense are related to coordination, while strength only will influence coordination at the onset of fatigue. Thus, since the tasks loaded on this component require well timed and well balanced functioning of several muscles during a single movement (Broer, 1973), this factor was named ‘movement coordination’. Component two consisted of the dynamic balance, hopping-in-square and quadrant jump motor skills. The loading for dynamic balance was high and, along with the quadrant jump, demonstrated components of agility. Both tasks also involve the capacity to change body position quickly and accurately (Brown, 2001). It is true that the strength component of the jump directly influences individual power (Fleishman, 1964). To perform this motor skill well, requires optimal balance control in an upright posture (Kollmitzer et al., 2000). However, the hopping-in-square task categorises dynamic balance because it requires posture control to perform the task (Liemohn & Knapczyk, 1984). If one rejects any interaction of speed and strength in the agility component (Hilsendager et al., 1969), and strength contributed in all extracted items, the naming of this factor as something other than agility is more appropriate. As these tasks require control and adaptable force to regulate the posture, this component was labelled ‘postural control’ (Burton & Davis, 1992; Kent, 1994). Component three consisted of the two motor skills assessing static balance - one-footbalance-with-eyes-open and one-foot-balance-with-eyes-closed. Both motor skills require one to maintain or control the centre of mass in relation to the base of support to prevent falling and complete the desired movements (Westcott et al., 1997). Also, being able to balance on one leg requires an ability to focus attention while inhibiting extraneous motor movements. Success in these two motor skills requires control of extraneous motor movements and centre of mass, especially with the eyes closed. Fleishman (1964) suggested 61 that skills measured with eyes open or closed, assesses gross body equilibrium. Given the static nature of these two skills, the factor was named ‘static balance’. The 3 component solution reported for the BMC instrument (i.e., movement coordination, postural control and static balance) is at odds with the intended 2-factor model (i.e., balance and movement coordination). At a more general level, the 2-factor model appears to adequately represent what the BMC motor skills measure. However, empirically this was not the case. It appears that more specific aspects of these motor skills, or perhaps important basic qualities of these skills, determined a 3 component solution. Six of the motor skills did load correctly on to their respective components (movement coordination ability - shuttle run, shuttle-run-with-object, hopping speed, zigzag run; balance ability - one-foot-balancewith-eyes-open and one-foot-balance-with-eyes-closed). The other three motor skills formed a separate component named postural control (i.e., dynamic balance, hopping-in-square and quadrant jump). Examining the 3 component solution suggests that the motor skills making up movement coordination, as a group, reflect a basic coordination of upper and lower body limbs while moving in a forward direction. However, the other two component s appear to assess different aspects of balancing ability – being able to stand perfectly still and being able to control one’s balance while moving in a confined area. This breakdown of balance into two related, but separate, aspects is important to help clarify what is being assessed by these motor skills. The two motor skills making up the static balance factor have been found to load together on a single factor in previous research (Bass, 1939; Burton & Davis, 1992). However, in this setting, the BMC assesses more than one aspect of balance. Despite the BMC being designed to assess two of Burton’s (1993) movement skill foundations, empirically it was found that the BMC not only does that, but also examines two aspects of balance rather than one. However, it is possible that the solution found for the BMC is only pertinent to the current sample. Therefore, it is recommended that these findings be validated on another sample. Summary: A series of PCA factor analyses were undertaken to explore the nature of the underlying constructs of the motor skill instruments of the MAND, AIS and BMC. It was found that the MAND assessed three motor ability component s (postural control, bimanual dexterity and muscle power); the AIS assessed one motor ability component (anaerobic power); and the BMC assessed three motor ability components (movement coordination, postural control and static balance). The motor skills and identified motor abilities from the three motor skill instruments are illustrated in Figure 3. 62 Heel Toe .71 Balance MAND .64 Finger Nose Finger .59 MAND Te s t Jumping Postural Control .52 Beads Rod .72 Beads Box .71 Nut Bolt .59 Bi-manual Dexterity 43.91% Rod Slide Grip Strength .77 Muscle Power Finger Tapping 40m Sprint .69 .75 AIS Te s t MSFT .70 Vertical Jump .64 Explosive Power Basketball Throw 42.9% .49 Shuttle Run .88 Shuttle Run Object .88 Hopping Speed .78 .71 Movement Coordination BMC Te s t Zigzag Run Dynamic Balance Hopping-in-Square Quadrant Jump .81 .76 .59 Balance Eyes Open .85 Balance Eyes Closed .73 Postural Control 66.3% Static Balance *MSFT – Multistage Fitness Test Figure 3. The motor skills, loadings & motor abilities for the MAND, AIS & BMC. 63 SECTION B – AN EXAMINATION OF GENERAL MOTOR ABILITY Section B examines the concept of GMA. Burton and Miller (1998) noted that, in order to assess motor skills adequately, at least two instruments, which assess unique motor skills, are needed. Thus, the AIS and BMC motor skills were examined together to constitute a combined AIS+BMC instrument. This combination provided a larger set of motor skills with which to test for GMA than using the AIS or BMC alone. Several approaches can be used to test for the existence of GMA (Burton & Richardson, 2001; Jensen & Weng, 1994; Johnson et al., 2004, 2008). The approach used here was higher order factor analysis (Rummel, 1970). A ‘g’ in motor ability was examined separately for boys and girls, as past research reported differences between boys and girls in their performances of fundamental movement skills (Seefeldt & Haubenstricker, 1982; Thomas & French, 1985; Thomas, Michael & Gallagher, 1994). Despite this, Burton and Miller (1982) noted that some research in motor ability typically ignores the possibility of gender differences at a higher level. Thus, recognising the possibility of gender differences, this study tested for the existence of a ‘g’ separately in boys and girls. Given the exploratory nature of these analyses, no formal hypotheses were made on the motor abilities arising from such an examination. However, from the first-order factor analysis of the AIS+BMC, the underlying factors, or specific motor abilities, can be subjected to a second order factor analysis to test for a motoric ‘g’. Statistical Analysis Procedure. Firstly, raw scores from the motor skill tests were transformed into z scores for each gender-by-age-group classification, then into T-scores to eliminate the effects of gender and age. The first-order factor analysis on the combined AIS+BMC motor skills used PCA with oblique PROMAX rotation. The oblique rotation is essential for further higher-order analysis as this rotation offers a continuous range of correlations between the factors (Tabachnick & Fidell, 1989). A higher-order factor analysis was then conducted to test for a ‘g’ in motor ability. For both the first-order and higher-order factor analyses, the interpretation of the first-order components and higher-order factor was based on the motor skills and components, respectively, loading ≥ .50 (Rummel, 1970). For the results testing for a motoric ‘g’ in all participants, see APPENDIX I on the CD. 4.3. RESULTS – BOYS’ SUB-SAMPLE The exploratory PCA factor analysis revealed four rotated components that accounted for 60.56% of variance. The eigenvalues, loadings and the intercorrelation matrix for the boys’ sub-sample are presented in Table 10. 64 4.3.1. First-Order Factor Analysis Component One: The variables that loaded on this component were shuttle run (.911), shuttle-run-with-object (.903), hopping speed (.817) and zigzag run (.673). Component Two: High loadings on this component were one-foot-balance-with-eyes-open (.709) and multistage fitness test (.536). Component Three: This component had loadings on dynamic balance (.770), quadrant jump (.756) and hopping-in-square (.709). Component Four: This component had high loadings on vertical jump (.841) and basketball throw (.641). 4.3.2. Higher-Order Factor Analysis The higher-order factor analysis extracted one factor accounting for 45.5% of variance. For eigenvalues, loadings and intercorrelation matrix for the higher-order analysis see Table 11. Table 10. Correlations, Components and Loadings of the AIS+BMC for the Boys. Component 1 Eigenvalue 2 3 4 4.30 1.44 1.11 1.03 Motor Skill 1 1. Shuttle run - 2 3 4 3. Hopping speed 4. Zigzag run 7 8 9 10 11 12 13 .63 .58 .20 .27 .30 .30 .29 .29 .22 .16 .30 .903 - .47 .16 .17 .22 .44 .22 .14 .19 .08 .28 .817 .117 -.119 - 5. One-foot balance with eyes open 6. Multistage fitness test 7. One-foot balance with eyes closed 8. 40m sprint 9. Dynamic balance 10. Quadrant jump 11. Hopping-in-square 13. Basketball throw 6 .92 .65 .59 .19 .11 .30 .29 .30 .30 .29 .22 .37 .911 2. Shuttle run/object - 12. Vertical jump 5 .18 .26 .33 .32 .30 .20 .22 .20 .30 .673 .175 - .11 .29 .29 .25 .07 .18 .22 -.01 - .709 .222 .17 .32 .18 .10 .15 .13 -.01 .263 .536 -.180 - .21 .25 .18 .17 .13 .06 .234 .470 .102 - .37 .21 .21 .23 .20 .199 .456 - .33 .47 .21 .11 - .239 .191 .770 .18 .08 .19 .114 -.273 .756 - .18 .08 -.100 .123 .709 - .26 -.159 .244 - .361 -.393 .841 .641 65 Note. Loadings ≥ .50 are in bold. Table 11. Higher-order Factor Analysis of the AIS+BMC for the Boys. Higher-Order Factor 1 Eigenvalue 1.82 % of variance 45.51 Component Component 3 3 1 4 2 - .39 .24 .28 .771 - .35 .34 .737 - .14 .601 - .566 Component 1 Component 4 Component 2 4.3.3. Discussion The PCA analysis on the boys identified four components that explained 60.56% of the variance in the solution. Two motor skills failed to reach the .50 cut-off level for inclusion; namely, the one-foot-balance-with-eyes-closed and the 40m sprint. The four motor skills that loaded onto the first component were shuttle run, shuttle-run-withobject, hopping speed and zigzag run. The task analysis on the shuttle run, shuttle-run-withobject and zigzag run; indicated that strength, speed, balance, agility and endurance components are necessary when performing these motor skills. Given the nature of these skills, it was reasoned that this component could be labelled ‘movement coordination’. Component two was made up of one-foot-balance-with-eyes-open and the multistage fitness test. Maintaining body balance (static and dynamic) and achieving equilibrium with the integration of sensorimotor input from large muscle groups are important components in these motor skills. It was noted that the motor skills of one-foot-balance-with-eyes-closed and the 40m sprint also loaded substantially, but were not included as they did not reach the cut-off level of .50. Given that successful performances of these skills require control of balance and orientation of the body in space (McCarron, 1982), this component could be labelled ‘kinaesthetic integration’. The three motor skills that loaded onto component three were dynamic balance, quadrant jump and hopping-in-square. All of these tasks are performed in an upright position and, subsequently, require strength and balance to maintain posture during the dynamic 66 movements needed for these tasks (Burton & Davis, 1992; Westcott et al., 1997). Accordingly, Kollmitzer et al. (2000) wrote that strength and balance were important components in postural control. Posture serves two main functions; ‘to remain inside the supporting surface’ and ‘as a reference frame for perception and action with respect to the external world’ (Massion, 1994 pg. 877). Therefore, since controlling body posture is an important aspect of this component it was named ‘postural control’. Finally, the motor skills of vertical jump and basketball throw loaded onto the final component. The vertical jump task was established as a test of explosive strength (Australian Sports Commission, 1998; Eisenmann & Malina, 2003; Fleishman, 1964; Larson, 1941; McCloy, 1968; Sargent, 1968). On the other hand, the basketball throw task is claimed to measure upper body strength (Australian Sports Commission, 1998), strength and/or coordination (Barrow, 1954; Barrow & McGee, 1964), and muscular strength and speed of movement (Arnheim & Sinclair, 1979). Hempel and Fleishman (1955) have proposed a ‘limb strength’ factor for tasks involving both arm and leg strength movements. Considering that these tasks demonstrated an ‘ability to mobilise quickly and effectively maximum energy or force’ (Fleishman, 1964, pg. 96), this component was labelled ‘explosive power’. Higher-Order Factor Analysis. The higher-order factor analysis conducted on the four components which emerged from the combined AIS+BMC (i.e., movement coordination, kinaesthetic integration, postural control and anaerobic power), revealed one higher-order factor. This higher-order factor accounted for 45.51% of the variance, and the loadings for the first-order factors ranged from .57 to .77. Given that one higher-order factor encompassed all of the first-order components it is suggested that this demonstrates the presence of a ‘g’ in motor skill ability for the boys. The motor skill tests, first-order components and higher-order factor for the boys’ sub-sample on the combined AIS+BMC is illustrated in Figure 4. 67 First-Order FA Higher-Order FA Shuttle Run Shuttle Run Object .91 .90 Movement Coordination Hopping Speed .82 Zigzag Run .67 .74 40m Sprint AIS+BMC Te s t MSFT .71 Dynamic Balance .77 Hopping-in-Square .71 Quadrant Jump .76 Basketball Throw .64 Vertical Jump .84 Balance Eyes Open .54 .77 Postural Control ‘g’ .60 Explosive Power .57 Balance Eyes Closed Figure 4. Kinaesthetic Integration The AIS+BMC motor skills, first-order components and higher-order factor for the boys. 4.4. RESULTS – GIRLS’ SUB-SAMPLE Three rotated factors were extracted in the exploratory PCA factor analysis and they accounted for 57.7% of variance. The eigenvalues, rotated factor loadings and the intercorrelation matrix are presented in Table 12. 4.4.1. First-Order Factor Analysis Component One: The variables that loaded on this component were the shuttle run with object (.851), shuttle run (.845), 40m sprint (.780), hopping speed (.722), zigzag run (.698), multistage fitness test (.675) and vertical jump (.633). Component Two: This component had loadings on hopping-in-square (.793), dynamic balance (.762) and basketball throw (.676). Component Three: High loadings on this component were one-foot-balance-with-eyes-open (.886) and one-foot-balance-with-eyes-closed (.699). 68 Table 12. Correlations, Components and Loadings of the AIS+BMC for the Girls. Component 1 Eigenvalue 1 1. Shut. Run/obj - 2 3 4 5 6 7 8 9 10 11 12 13 .73 .47 .52 .51 .41 .26 .17 .25 .20 .32 .12 .25 .851 -.189 2. Shuttle run - .57 .68 .57 .50 .36 .30 .34 .31 .39 .17 .35 .845 3. 40m sprint - 4. Hopping speed .55 .56 .48 .30 .27 .27 .16 .32 .14 .28 .780 - .70 .57 .35 .30 .40 .28 .44 .28 .32 .722 .106 .135 5. Zigzag run - 6. Multistage fitness test .52 .32 .39 .40 .24 .39 .16 .27 .698 .179 - .33 .26 .27 .26 .35 .15 .25 .675 7. Vertical jump - 8. Hopping-in-square .15 .23 .15 .17 -.03 .13 .633 - 9. Dynamic balance .39 .32 .29 .12 .17 - 10. Basketball throw .762 .23 .15 .14 - 12. One-foot balance with eyes open .676 .23 .24 .148 .499 .198 - 13. One-foot balance with eyes closed .36 -.159 - .184 Note. Loadings ≥ .50 are in bold. Higher-Order Factor Analysis A higher-order factor analysis extracted one factor accounting for 59.5% of the variance. The eigenvalues, percentage of variance, component loadings and intercorrelation matrix are presented in Table 13. Higher-order Factor Analysis of the AIS+BMC for the Girls. Higher-Order Factor 1 Eigenvalue 1.78 % of variance 59.47 Components Component 1 Component 2 Component 3 1 2 3 - .54 .33 .833 - .29 .803 - .668 -.361 .793 .28 .46 .12 .19 - 11. Quadrant jump Table 13. 3 5.07 1.26 1.17 Motor Skill 4.4.2. 2 .886 .699 69 4.4.3. Discussion The exploratory Principal Component Analysis reduced the 13 motor skills of the combined AIS+BMC to 3 components that explained 57.67% of total variance. The tests loading on component one were shuttle-run-with-object, shuttle run, 40m sprint, hopping speed, zigzag run, multistage fitness test and vertical jump. A task analysis on the skills showed an agility component (for the shuttle run, the shuttle-run-with-object & the zigzag run), speed, strength and balance maintenance components (for the 40m sprint & hopping speed tests), another strength component (for the vertical jump) and endurance component (for the multistage fitness test). As these skills combine the interrelationships between strength, speed, balance, agility and endurance components, the component was labelled ‘movement coordination’. The motor skills of hopping-in-square, dynamic balance, basketball throw and quadrant jump loaded onto component two. A task analysis of these skills highlighted the requirements of coordination and balance while maintaining a vertical position. The basketball throw purportedly assesses upper body strength (Australian Sports Commission, 1998) but one needs to maintain balance and good posture throughout the throw in order to perform the skill well. Balance and strength appear to be major characteristics of this factor and these are important aspects of postural control (Kollmitzer et al., 2000). As the motor skills loading on this component are performed in an upright position, strength and balance are required to maintain posture during the dynamic movements needed to accomplish these tasks (Burton & Davis, 1992; Westcott et al., 1997). Therefore, controlling body posture is important for these motor skills and this component was named ‘postural control’. Component three included one-foot-balance-with-eyes-closed and one-foot-balance-witheyes-open. Fleishman (1964) suggested that skills measured with eyes open or closed assess gross body equilibrium. Tests loading here indicated an ability to maintain vertical balance while static and was labelled ‘static balance’ (Bass, 1939; Burton & Davis, 1992) Higher-Order Factor Analysis. The higher-order factor analysis conducted on the three identified components from the combined AIS+BMC (i.e., movement coordination, postural control and static balance) extracted one factor. This higher-order factor accounted for 59.47% of the variance, and the loadings for the first-order components ranged from .67 to .83. Given that one higher-order factor encompassed all of the first-order factors, it is suggested that this demonstrates the presence of a ‘g’ in motor skill ability for the girls. The AIS+BMC motor skills, first-order components and higher-order factor for the girls are illustrated in Figure 5. 70 First-Order FA Higher-Order FA Shuttle Run Shuttle Run Object Hopping Speed Zigzag Run 40m Sprint .85 .85 .72 .69 .78 .83 AIS+BMC Te s t .68 .63 MSFT Dynamic Balance .76 Hopping-in-Square .79 Quadrant Jump Movement Coordination Postural Control .81 ‘g’ .68 Basketball Throw Vertical Jump .67 Balance Eyes Open Balance Eyes Closed Figure 5. .89 .69 Static Balance The AIS+BMC motor skills, first-order components and higher-order factor for the girls. 4.5. DISCUSSION – GMA ANALYSES The first-order factor analyses conducted on the combined AIS+BMC revealed three components for the adolescent girls. Given the nature of the motor skills reported and that found for the exploratory factor analysis of the BMC, they were labelled similarly movement coordination, postural control and static balance. Although unanticipated, it is not surprising that the three components emerging from the exploratory factor analysis of the BMC are also present in the combined AIS+BMC analyses given that the BMC has twice as many motor skill tests as the AIS. Despite this imbalance, four first-order components were found for the adolescent boys. However, two of these components were similar to those found for the girls - movement coordination and postural control. The other two factors were different, kinaesthetic integration and explosive power. 71 The AIS+BMC analyses extracted quite similar motor abilities. In particular, movement coordination and postural control were found in each analysis and some balancing ability also emerged. The adolescent girls’ sub-sample assessed static balance, whereas a more general balance factor emerged for the adolescent boys, that of kinaesthetic integration. This balance ability for the boys is quite general in nature as it requires one to maintain balance both while standing still and when changing direction at speed. The final motor ability found only for the adolescent boys was explosive power. This suggested that, when assessing some forms of motor skill, power appears to be more relevant for adolescent boys. Past research has noted gender differences in motor skills and gender should be considered. These findings support that notion and suggest that gender differences could also occur at the motor ability level. Therefore, researchers need to be aware that a motor skill instrument may assess different things according to the gender being examined. Moderate to high loadings were demonstrated (ranging from .56 to .87) on each higher-order factor extracted from the second-order factor analyses. These factors suggested the existence of a ‘g’ in motor ability and, in this case, a ‘g’ associated with the AIS+BMC instrument. Such higher order analyses are rare and previous studies have not usually taken the next step to examine for the existence of ‘g’ in motor ability. With more sophisticated analysis tools available, some researchers have begun to examine for the existence of ‘g’. For instance, Chaiken, Kyllonen and Tirre (2000) re-analysed Fleishman’s 1954 psychomotor data to investigate a ‘g’ in psychomotor ability. Fleishman (1954) found four psychomotor abilities in his exploratory factor analytic approach in which the unrotated solution factor loadings were then rotated to reveal a simple structure. Such an approach was typical of the time and didn’t allow the examination of the data beyond this first-order level. Chaiken et al. (2000) tested whether these four factors could be nested within a psychomotor ‘g’. Using confirmatory factor analysis, they found evidence for a ‘g’ in psychomotor ability. A strength of the Chaiken et al. (2000) study was the examination of a large set of psychomotor skills that were associated with four psychomotor abilities. This allowed for a greater opportunity to test for the existence of ‘g’ in psychomotor ability. The current study only examined two motor skill instruments encompassing thirteen motor skills. Even so, from this small pool of motor skills, specific abilities were extracted which enabled an examination of ‘g’ and concluded that a ‘g’ in motor ability existed. However, if the AIS instrument alone was studied, can it be said that the single first-order component extracted is a ‘g’ element, or is it an aspect of power ability? Thus, future research needs to include a greater number of motor skill instruments in order to study ‘g’ in motor ability in greater detail. 72 Some studies into ‘g’ in general intelligence have reported a null sex difference in the types of ability found ( Aluja-Fabregat, Colom, Abad & Juan-Espinosa, 2000; Colom et al., 2000) and others have found gender differences in the abilities revealed (Jorm, Anstey, Christensen & Rodgers, 2004). Although contradictory findings also have been shown when examining mental ability, scholars have suggested that the biological and socio-cultural issues could influence ‘g’ (Jorm et al., 2004; Richardson, 1997). Given that view concerning general intelligence, it could well be that biological, socio-cultural and environmental issues will also influence motor ability. In the current research, gender was examined as a potential influence. The findings suggested that the AIS+BMC motor skill instrument assesses similar motor abilities in boys and girls – movement coordination, postural control and balance, on the whole. The AIS+BMC also assessed power ability for the boys thereby demonstrating gender differences in the motor abilities assessed. However, when these motor abilities underwent further factor analysis, only one ‘g’ element was found for each gender. The variance differences found for the boys’ (45.51) and the girls’ (59.47) is unclear, but possibly can be explained by different sample sizes. One also needs to examine the relatedness of the ‘g’s found for the girls and boys, given that the AIS+BMC was a newly constructed instrument. Finally, it should be noted that the percentage of variance accounted for is tolerable but not strong, and 40% for the girls and 55% for the boys remains unexplained. Some of the unexplained variance could be due to motivation, practice and opportunity. Future investigations could consider also the influence of genetic variables such as speed in conjunction with variables not necessarily impacting on sport performance (e.g., static balance). Therefore, whether the ‘g’ found for the girls and boys represents a more general ‘g’, awaits further examination. In summary, whilst the analyses did not provide definitive evidence for the existence of GMA, neither did it deny the existence of a motoric ‘g’. Further research is needed to clarify this issue. There were gender differences in the motor abilities assessed by the AIS+BMC. Therefore, researchers need to be aware that a motor skill instrument may assess different things according to the sample under investigation. Additionally, the gender differences found in the motor abilities assessed by the AIS+BMC need further investigation before one can be confident in the veracity of this finding. Finally, despite gender differences reported in the motor abilities assessed by the AIS+BMC, these differences did not impact on finding a single higher-order factor, and subsequent existence of a ‘g’ in motor ability as assessed by the AIS+BMC. The hierarchical models (Jensen & Weng, 1994; Rummel, 1970) found in this study are described in Table 14. 73 Table 14. The First-order Components and Higher-order Factor of the AIS+BMC for the Boys’ and Girls’ Sub-samples. Boys Girls First-order Components Movement coordination Movement coordination Kinaesthetic Integration Postural control Postural control Static balance Explosive Power Higher-order Factor ‘g’ 4.6. ‘g’ GENERAL DISCUSSION Burton and Miller (1998) have recommended examining the factorial validity of motor skill instruments and this is especially relevant when the sample under investigation is different in nature from that used to establish the instrument. Because this was the case in the current study, the factorial validity of the MAND, AIS and BMC motor skill instruments was examined in the first section of this chapter. The factor analyses of the MAND, AIS and BMC produced factor structures that were different from those purported by their authors. Factor analysis allows the examination of the factorial validity of the motor skill instruments and can provide an empirical solution for each unique situation. If the factor structure is the same, but a reduced set of motor skills are relevant, then one can be confident in the author’s description of the instrument. However, if the factor structure changes from sample to sample, care is needed to present the findings in light of these changes and recognise that the findings may be sample specific. It was noted that the three factors found for the BMC were also found in the combined AIS+BMC. This suggested that the BMC factors appeared to be relatively stable in this sample. Indeed, the motor skills making up the factors found for the BMC also made up the similarly named factors in the AIS+BMC analyses. However, the AIS test appears not to be as stable. Of the four motor skills assessing explosive power, only the multistage fitness test was found to load onto a component (i.e., movement coordination for the adolescent girls and general balance for the boys). The other three motor skills were inconsistent in their loading pattern, although when they did load onto a component, their inclusion was not inconsistent with the overall nature of that factor. However, an explosive power ability type, which is what the AIS seems to assess in this sample of Malaysian 74 adolescents, was only found in the boys. In spite of this, it is quite satisfying that the AIS+BMC analyses extracted the motor abilities of movement coordination and postural control for the girls and the boys. However, two other abilities were also reported for the boys that were quite different from those reported for the adolescent girls, namely, kinaesthetic integration and explosive power. Whether, these three and four component solutions can be verified with other samples awaits further investigation. However, the results of the current research seem to suggest that Burton and Miller’s (1998) recommendation for examining the psychometric properties of an instrument appears warranted and that recognising gender differences is also warranted. Finally, despite finding specific sets of motor abilities for the motor skill instruments it should be noted that the percent of variances in each case are reasonable but not outstanding. There is still a sizeable chunk of variance unaccounted for in each case, which may be just as important (e.g., practice, motivation & genetics). This cautionary note is also relevant for the ‘g’ analyses in that up to 50% of the variance was unaccounted for in each case. A possible reason for the factor analyses not producing great results and different to those reported in other research could be due to the homogeneity of the sample (i.e., small sample size, small age range, no special needs participants, no special athletic participants). Unfortunately, these limitations were unable to be avoided and future research needs to take these points into consideration. Burton and Rodgerson (2001) presented a taxonomy of movement skills and general motor ability made up of four levels – movement skills, movement skill sets, movement skill foundations and general motor ability. These four levels are presented in a hierarchical structure where movement skills at the first level can be grouped into movement skill sets at the second level. Underlying both movement skills and movement skill sets, sits movement skill foundations. Basic movement skill foundation areas are thought to influence skilled performance from the third level. Finally, at the fourth level and underlying all, is GMA. Burton and Rodgerson (2001) wrote that GMA manifests itself in just about all movement situations by drawing the movement skill foundations together to perform efficiently in the face of complexity. Additionally, GMA can be inferred by performance on either motor skills or movement skill sets but, as with movement skill foundations, is not in itself a movement skill or combination of skills (Burton & Rodgerson, 2001). Keeping this taxonomy in mind, Section Two of this chapter set out to find a ‘g’ in motor ability. For these analyses, the BMC and AIS were analysed together. It was anticipated that by combining the BMC with the AIS this would provide a more comprehensive examination of motor ability via a larger pool of motor skills. Additionally, the factor analysis of the BMC found that this motor skill instrument assessed three motor abilities that differed from the 75 one assessed by the AIS. The 13 movement skills of the AIS+BMC extracted two sets of movement skill sets – movement coordination, postural control and static balance for the adolescent girls; movement coordination, postural control, kinaesthetic integration and explosive power for the adolescent boys. The higher-order factor analyses of these extracted movement skill sets did reveal a ‘g’ in motor ability. The finding of ‘g’ in this manner supports the hierarchical nature of Burton and Rodgerson’s (2001) taxonomy – that a ‘g’ in motor ability can be inferred by performance on either movement skills or movement skill sets. However, the author in this study considers this ‘g’ to be a ‘g’ that is associated with the motor skills assessed by the AIS+BMC. It is highly likely that other ‘g’s will be found from the different motor skill instruments. Subsequent examination of these ‘g’s will advance research closer to establishing the existence of GMA. Thus, this chapter set out to examine the factorial validity of motor skill instruments used in the current research and to find ‘g’ in motor ability. The higher-order factor analyses of the AIS+BMC motor skill set supported the existence of a ‘g’ in motor ability, thereby adding to the growing awareness of this ‘g’ in human behaviour. Factorial validation analyses indicated that such an analysis was warranted given that the instruments assessed something different from that purported by their authors. Thus, one can talk about what a particular motor skill instrument assesses at a more general level but that was not the main thrust of the current research. The overall drive of the current research was to build on previous work surrounding identification of athletic talent in Malaysia and, primarily, to initiate the development of a TI instrument relevant to Malaysians. Past work into identifying athletic talent in Malaysia used the AIS motor skill instrument. Although the authors of the AIS purport that this instrument measures four components of motor ability, this study found that it only assesses one type of motor ability – explosive power. Since the aim was to develop a TI instrument that provides a more rounded assessment, it was decided to refer to a checklist of movement skill foundations hypothesised to be important in the execution of movement skills (Burton and Miller, 1998). Subsequently, nine motor skills were selected that assessed two of these foundations – movement coordination and balance. This new instrument was called Balance and Movement Coordination, and it was anticipated that the combined BMC and AIS batteries would create a more comprehensive examination of motor ability for TI in Malaysia. Whether this combination will be helpful to identifying athletic talent is beyond the scope of the current research. For the remainder of the thesis the focus turns to the motor skills themselves, since performance on the motor skills is what counts when identifying athletic talent. Chapter Five will examine the descriptive data and provide some normative data for future reference; and an examination of age and gender on motor performance also follows. Comparisons with what is found in these analyses here will be undertaken for the 76 MAND and the AIS. Then, Chapter Six seeks to establish motor skills that could help in identifying athletic talent. Specifically, motor skills are sought that can reliably discriminate the adolescents into a) three motor coordination groups derived from scores on the MAND, and b) three motor ability groups derived from the scores on ‘g’. 77 CHAPTER 5 RESULTS AND DISCUSSION FOR THE MOTOR SKILL PERFORMANCES Unless otherwise stated the participant’s raw score for the motor skills making up the MAND, AIS and BMC were utilised in the following analyses. There were 26 separate ANOVAs performed on the data and an overall Bonferroni correction was applied to all effects. Thus, the overall p value used was p < .002. The results are organised into three sections: i) basic height, weight, and BMI information and performances on four motor skills assessed via the AIS instrument; ii) fine and gross motor skill performances measured via the MAND; and iii) balance and movement coordination motor skill performances assessed via the BMC. Within each section, basic Descriptive statistics are detailed and followed by a series of ANOVAs. To aid in the presentation of results, the participants were classified according to gender and age. This resulted in eight sub-groups. The girls were classified into: girls aged 12 (G12), girls aged 13 (G13), girls aged 14 (G14) and girls aged 15 (G15). The boys were classified as: boys aged 12 (B12), boys aged 13 (B13), boys aged 14 (B14) and boys aged 15 (B15). The chapter concludes with a discussion of the findings. 5.1. AUSTRALIAN INSTITUTE OF SPORT (AIS) TALENT IDENTIFICATION INSTRUMENT The AIS instrument records information regarding basic anthropometic measures of height and weight; and motor skill performance for the 40m sprint, vertical jump, basketball throw and the multistage fitness test. Initially, the results of the reliability analysis of the AIS motor skills are presented. Then the Descriptive and ANOVA results are presented separately for the anthropometry and motor skill assessments. 5.1.1. Reliability of the AIS The results showed that AIS had very good test re-test reliability with all tests exhibiting coefficients ≥ .92 (see Table 15). In particular, the 40m sprint and t he basketball throw recorded very high reliability scores. The average r across all the AIS motor skills was .95. This analysis indicates that reliability of the motor skills on the AIS is acceptable, and can be used with Malaysian adolescents. 78 Table 15. Means ± SDs and Reliability Coefficients for the AIS Tests. Testing Session First Second Variables Mean SD Mean SD r Basketball Throw (m) 4.55 1.15 4.60 1.19 .98 Vertical Jump(cm) 24.61 7.42 24.45 7.04 .94 40m Sprint(s) 8.10 1.12 8.09 1.15 .97 Multistage Fitness Test (laps) 12.24 4.12 12.10 4.65 .92 5.1.2. Anthropometry Tests Descriptives Table 16 presents the Means ± SDs for the anthropometry measures. The mean heights of boys increased more rapidly with age than those for girls. The mean heights of girls increased from 12-14 years (G12-14), but were unchanged at age 15 years (G15). The mean weights for boys increased in parallel with heights, as did the mean weights for girls, including the G15s. The BMIs of the G12-14s years were higher than boys of similar ages. However, at 15 years, the BMI of boys was similar to that of the girls, having increased rapidly between 14 and 15 years old. ANOVAs A series of two (gender) by four (age) way ANOVAs were conducted to determine whether there were any significant differences on the height, weight and body mass index for these groups (see Table 17). The results revealed significant gender-by-age interaction for height (p < .001) and an age main effect for weight (p < .001). The gender by age interaction explained how an expected increase in height was evident for both boys and girls, but this was more so with the boys. Specifically, all of the older boy age groups were significantly taller than their younger counterparts. For the girls the G12s were significantly shorter than the G14s and G15s. The age main effect for weight indicated that the adolescent’s weight increased as they got older. Specifically, the post-hoc analysis revealed that the 15-year-olds were heavier than all age groups and that the 14-year-olds were heavier than the 12-yearolds (see Table 18). 79 Table 16. Means ± SDs for the AIS Anthropometry Measures. Age Height (m) Weight (kg) BMI (kg/m2) Boys Girls (years) Mean SD Mean SD 12 1.48 a b c d .08 1.50 a .06 13 1.55 a b c d .09 1.53 .06 14 1.60 a b c d .08 1.56 a .05 15 1.65 a b c d .06 1.56 a .06 12 39.96 10.09 45.78 13.70 13 46.60 14.14 46.20 13.99 14 47.17 11.36 48.53 9.95 15 59.06 18.01 51.58 11.70 12 18.14 4.03 20.22 5.33 13 19.25 4.43 19.63 5.42 14 18.44 3.84 20.01 3.81 15 21.58 5.89 21.09 4.65 Note. ns, B12 = 55, B13 = 53, B14 = 41, B15 = 16, G12 = 37, G13 = 54, G14 = 49, G15 = 25. Same superscript letters indicate significant differences within group pairwise comparisons. Same subscript letters indicate significant differences between group pairwise comparisons. Bolded letters indicate the focus for the comparisons being made (i.e.,. a = B12 and G12, b = B13, c = B14, d = B15). A Bonferroni correction is used for all post-hoc comparisons. 80 Table 17. ANOVA Results for the AIS Anthropometry Measures. Height Weight Body Mass Index Table 18. Weight Effect df F Sig. Gender 1/322 17.872 .001 Age 3/322 38.511 .001 Gender by Age 3/322 7.511 .001 Gender 1/322 .005 .943 Age 3/322 9.221 .001 Gender by Age 3/322 2.806 .040 Gender 1/322 3.407 .066 Age 3/322 2.087 .102 Gender by Age 3/322 1.007 .390 Descriptives for the Main Effect Age on the AIS Weight Assessment. n Age Mean SD CI 92 12 41.11*# 12.10 39.60 – 44.62 107 13 46.40# 13.99 43.72 – 49.08 90 14 47.91*# 10.65 45.68 – 50.14 41 15 54.52# 15.02 49.78 – 59.27 Note. * denotes significant difference found between the 12-year-olds and the 14 year olds. # denotes a significant difference found between the 15-year-olds and all other age groups. CI = 95% Confidence Interval. 81 5.1.3. Motor Skill Performances Descriptives The older boys and girls generally threw the basketball further than the younger groups (see Table 19). For the vertical jump, the older participants typically jumped higher than their younger cohorts. The 40m-sprint performance also tended to improve with age for both boys and girls. Finally, the multistage fitness test performances were relatively stable for the boys with the exception of the B15s. The girls’ multistage fitness test performances were varied across the age groups. ANOVAs Table 20 presents the results of the two-way ANOVAs for the four AIS motor skills. A significant gender-by-age interaction was found for basketball throw (p < .001) and significant main effects for gender (i.e., vertical jump and 40m sprint) and age (i.e., vertical jump) (all ps < .001). Interaction Effects Basketball Throw. The simple effect analysis on basketball throw showed that the B12 group threw a significantly shorter mean distance than the other boys (Effect sizes: .75, 1.34, and 2.61, for B13, B14 and B15, respectively). The B13 group also threw a significantly shorter mean distance than the B15 group (Effect size: 1.51), but threw further than the G12, G13 and G14 groups (Effect sizes: 1.26, .91, and .93, respectively). The B14 group showed significantly better performances than all of the girl groups (Effect sizes: 2.07, 1.64, 1.61, and 1.38, for G12, G13, G14 and G15, respectively) but had a shorter mean distance score than the B15 group (Effect size: 1.15). The B15 group showed a significantly better distance performance when compared with any of the age groups. No significant differences in basketball throwing distance were found for the within-girl age group analysis. Figure 6 graphs the significant age-by-gender interaction for the basketball throw. 82 Table 19. Means ± SDs for the AIS Motor Skills. Boys Girls Age Mean SD Mean SD 12 4.41 a d 1.03 3.96 b c d .63 13 5.26 a b d b 1.23 4.33 b c d .76 14 5.83 a c d c 1.09 4.27 b c d .86 15 7.02 abcd d .89 4.51 .69 12 24.98 5.25 21.51 4.30 13 27.40 6.59 24.50 6.56 14 28.80 9.04 22.51 5.51 15 35.63 8.29 25.68 6.49 12 7.58 .62 9.17 1.48 13 7.53 .64 8.87 1.33 14 7.41 .60 8.34 1.03 15 7.43 .95 8.35 1.05 Multistage Fitness Test 12 13.87 4.50 10.43 3.25 (laps) 13 13.91 5.17 13.76 5.53 14 13.88 4.56 11.64 4.76 15 11.56 3.48 13.40 3.50 Basketball Throw (m) Vertical Jump (cm) 40m sprint (s) cd Note. ns, B12 = 55, B13 = 53, B14 = 41, B15 = 16, G12 = 37, G13 = 54, G14 = 49, G15 = 25. Same superscript letters indicate significant differences within group pairwise comparisons. Same subscript letters indicate significant differences between group pairwise comparisons. Bolded letters indicate the focus for the comparisons being made (i.e.,. a = B12, b = B13, c = B14, d = B15). A Bonferroni correction is used for all post-hoc comparisons. 83 Table 20. ANOVA Results for the AIS Motor Skills. Basketball Throw Vertical Jump 40m sprint Multistage Fitness Test Effect df F Sig. Gender 1/322 145.25 .001 Age 3/322 28.16 .001 Gender by Age 3/322 12.74 .001 Gender 1/322 53.19 .001 Age 3/322 11.94 .001 Gender by Age 3/322 3.54 .015 Gender 1/322 100.02 .001 Age 3/322 4.51 .004 Gender by Age 3/322 1.92 .127 Gender 1/322 3.23 .073 Age 3/322 2.36 .072 Gender by Age 3/322 3.93 .009 Basketball Throw 9 Meters 7 5 3 1 12 13 14 15 Age (years) Boys Figure 6. Girls Significant age by gender interaction for the Basketball throw. 84 Main Effects Vertical jump. There was a significant main effect for gender, F(1,322) = 53.19, p < .001, with the boys jumping higher than the girls (Boys, M = 27.74 ± 7.61 and Girls, M = 23.42 ± 5.94; Effect size: .63; 95% CI 26.57 – 28.91 and 22.51 – 24.33, respectively). A significant main effect was also found for age F(3,322) = 11.94 p < .001. The post-hoc analysis on the age groups showed that the 15-year-olds jumped higher compared to the other agegroups (Effect sizes: .93, .50, and .51, for 12-, 13- and 14-years, respectively) (see Table 21). 40m Sprint. For the 40m sprint, there was a significant main effect of gender, F(1,322) = 100.02, p < .001, with the boys running quicker times than the girls (Boys, M = 7.51 ± .66s and Girls, M = 8.71 ± 1.28s; Effect size: 1.18; 95% CI 7.41 – 7.61 and 8.51 – 8.89, respectively). Table 21. Vertical Jump Descriptives for the Main Effect Age on the Vertical Jump Motor Skill. n Age Mean SD CI 92 12 23.59# 5.16 22.52 – 24.66 107 13 25.93# 6.70 24.65 – 27.22 90 14 25.38# 7.94 23.72 – 27.04 41 15 29.56# 8.67 26.83 – 32.30 Note. # denotes a significant difference found between the 15-year-olds and all other age groups. CI = 95% Confidence Interval. 5.2. McCARRON ASSESSMENT OF NEUROMUSCULAR DEVELOPMENT (MAND) The MAND instrument records information regarding fine and gross motor skills. The fine motor skills include putting beads in a box, placing beads on a rod, finger tapping, turning a bolt into a nut, and sliding a peg along a rod. For the gross motor tasks the skills are grip strength, finger-nose-finger, two-feet jumping for distance, heel-toe walking, and balancing. Initially, the results of the reliability analysis on the MAND are reported. Then the Descriptive and ANOVA results are presented separately for the fine motor and gross motor tests. 85 5.2.1. Reliability of the MAND The Means ± SDs for the analysis are presented in Table 22. The results show that the MAND had good test-retest reliability with a Cronbach alpha range of .72 for finger tapping to .97 for jumping. In particular, the skills of jumping, finger-nose-finger, balance, and nut and bolt tests had reliability scores≥ .90. There was an average of r = .86 across all tests. This analysis indicates that reliability of the test items on the MAND is acceptable, and can be used to examine fine and gross motor skills in Malaysian adolescents. 5.2.2. The Neuromuscular Development Index The Neuromuscular Development Index (NDI) is an index of fine and gross motor skill level. The motor skills raw scores were initially scaled, then summed, and then converted using the tables provided by McCarron (1982). The NDI is based on a distribution with a mean score of 100 and a standard deviation of 15. The age group Means and SDs for the Boys were B12 - M = 111.2 ± 15.11, B13 - M = 114.5 ± 14.6, B14 - M = 108 ± 16.31, and B15, M = 104.9 ± 13.64. The Girls’ age group NDI Means ± SDs were G12 - M = 108.8 ± 11.93, G13 - M = 101.7 ± 15.59, G14 - M = 106.2 ± 17.44, and G15 - M = 91.2 ± 10.10. Table 22. Means ± SDs and Reliability Coefficients for the MAND. Testing Session First Second Variables Mean SD Mean SD r Beads in Box 53.45 4.70 52.42 5.26 .89 Beads on Rod 26.21 2.88 26.24 3.27 .82 Finger Tapping 90.06 11.17 92.61 10.83 .72 Nut and Bolt 166.42 5.964 167.03 6.12 .90 Rod slide 87.55 6.06 87.12 5.45 .77 Grip strength 44.45 8.52 44.30 7.84 .87 Finger-nose-finger 69.39 6.48 69.21 6.426 .95 Jumping 72.76 12.36 73.36 11.89 .97 Heel-toe 37.67 2.80 38.06 2.36 .74 Balance 96.73 18.82 100.39 18.93 .93 86 5.2.3. Fine Motor Skills Descriptive and ANOVA analyses were conducted to describe, and also determine, if performances on the MAND fine motor skills differed with gender and age. The raw scores reported for each motor skill, and not the MAND scaled scores, were used in these analyses. Descriptives Table 23 reports the Means and SDs for the MAND fine motor skills. The results indicate that the girls placed more beads in the boxes and beads on rods than the boys in all age groups. The finger tapping performance, however, showed the boys outperforming the girls in each age group. The girls tended to score higher than boys for the nut and bolt test except for G14s who achieved similar scores. Results for the rod slide indicated that both the boy and girl groups showed varied rod slide performances. ANOVAs The two (gender) by four (age group) ANOVA results presented in Table 24 reveal no significant gender-by-age interactions. However, there were significant main effects for both gender and age. Main Effects Gender. Specifically, significant gender effects were found for the fine motor skills of: beads in box and beads on rod (ps < .001). The results showed that the girls performed significantly better than the boys for beads in box (Girls, M = 56.99 ± 6.04 and Boys, M = 54.3 ± 5.62; Effect size: .46; 95% CI 56.06 – 57.92 and 53.44 – 55.17, respectively) and beads on the rod (Girls, M = 27.82 ± 2.46 and Boys, M = 26.20 ± 2.67; Effect size: .63; 95% CI 27.45 – 28.20 and 25.79 – 26.61, respectively). Age. For age, significant main effects were found for the fine motor skill finger tapping (p < .001). The post hoc analysis revealed that the 13-year-olds group (M = 90.39 ± 13.17) performed significantly better than the younger group aged 12 years (M = 82.85 ± 9.93; Effect size: .64) and the older group aged 14 years (M = 82.77 ± 12.0; Effect size: .60) (see Table 25). 87 Table 23. Means ± SDs for the MAND Fine Motor Skills. Age Beads in Box Beads on Rod Finger Tapping Nut and Bolt Rod slide Boys Girls (years) Mean SD Mean SD 12 53.29 4.29 55.65 4.81 13 54.74 5.43 55.15 5.82 14 54.76 7.68 59.16 6.54 15 55.19 3.73 58.68 5.60 12 26.36 2.47 27.27 2.49 13 26.04 3.13 27.63 2.22 14 26.34 2.67 28.10 2.50 15 25.81 1.72 28.52 2.71 12 83.24 9.29 82.27 10.93 13 92.26 12.85 88.56 13.34 14 86.51 12.07 79.63 11.13 15 87.38 11.75 83.48 11.74 12 166.20 5.48 168.95 4.97 13 165.02 5.30 167.39 6.17 14 167.98 6.39 167.20 5.03 15 164.56 5.01 165.68 4.15 12 85.02 9.70 87.35 5.38 13 89.32 3.24 87.24 6.50 14 89.02 3.44 89.47 3.35 15 88.25 3.79 87.68 3.52 Note. ns, B12 = 55, B13 = 53, B14 = 41, B15 = 16, G12 = 37, G13 = 54, G14 = 49, G15 = 25 88 Table 24. ANOVA Results for the MAND Fine Motor Skills. ANOVA Variables Effect df F Sig. Beads in Box Gender 1/322 15.14 .001 Age 3/322 4.01 .008 Gender by Age 3/322 2.11 .099 Gender 1/322 31.96 .001 Age 3/322 .57 .638 Gender by Age 3/322 1.17 .322 Gender 1/322 7.58 .006 Age 3/322 9.15 .001 Gender by Age 3/322 .95 .418 Gender 1/322 4.34 .038 Age 3/322 2.86 .037 Gender by Age 3/322 1.91 .128 Gender 1/322 .002 .963 Age 3/322 4.50 .004 Gender by Age 3/322 2.51 .059 Beads on Rod Finger Tapping Nut and Bolt Rod slide Table 25. Finger Tapping Decriptives for the Main Effect Age on the Finger Tapping Motor Skill. n Age Mean SD CI 92 12 82.85# 9.93 80.79 – 84.90 107 13 90.39# 13.17 87.87 – 92.92 90 14 82.77# 12.00 80.25 – 85.28 41 15 85.00 11.76 81.29 – 88.71 Note. # denotes a significant difference found between the 13-year-olds and the 12- and 14year-old age groups. CI = 95% Confidence Interval. 89 5.2.4. Gross Motor Skills Descriptive and ANOVA analyses were conducted to describe, and also determine, if performances on the MAND fine motor skills differed with gender and age. The raw scores reported for each motor skill, and not the MAND scaled scores were used in these analyses. Descriptives Table 26 reports the Means ± SDs for the MAND gross motor skills. For the Grip Strength skill, the results showed increases in grip strength for both boys and girls with an increase in age and that the boys scored higher than girls for this skill at every age. A similar pattern also was found for the Jumping skill by the adolescents. The Finger-nose-finger skill results were varied across the age groups. For the Heel-toe tandem walk, the performances of the boys were stable across the age groups with the girls reporting varied performances. Finally, the mean Balance times for girls aged 13 years and above were better than any of the boy age groups, with the boys demonstrating similar times across the age groups. ANOVAs A series of two (gender) by four (age) ANOVAs examined whether performances on each gross motor item differed across the gender and age groups (see Table 27). Significant age by gender interactions were found for two of the gross motor skills: Grip strength (p < .001) and Finger-nose-finger (p < .001). Figure 7 plots the significant interactions. Main effects for Jumping (age and gender) and for Heel-toe (gender) (ps < .001). Interaction Effects Grip Strength. The simple effects analysis showed that the B15 and the B14 groups performed significantly better than the younger aged boy groups (B15 Effect sizes: 2.87, 1.78, and .98 for B12, B13 and B14, respectively and B14 Effect sizes: 1.49 and .71 for B12, and B13, respectively) and all of the girl groups (B15 Effect sizes: 3.11, 3.50, 2.86, and 2.42 for G12, G13, G14, and G15, respectively and B14 Effect sizes: 1.59, 1.58, 1.18, and .97 for G12, G13, G14, and G15, respectively). The B13 group also performed significantly better than the B12 group (Effect size: .71) and G12 group (Effect size: .82). No significant differences in grip strength were evident between the girl age groups. Finger-nose-finger. The simple effects analysis revealed that the B12 group performed significantly better than the B13, B14, G13 and G15 groups (Effect sizes: 1.12, 1.02, 1.80, and 2.12, respectively). Additionally, the B14 group also performed significantly better than the G15 group (Effect size: .61). The B15 group did significantly better than the 90 Table 26. Means ± SDs for the MAND Gross Motor Skills. Age Boys Girls (years) Mean SD Mean SD 12 39.84 b c d 9.85 38.73 b c d 8.79 13 47.79 b c d b 12.38 40.87 c d 6.66 14 56.93 c dc 13.42 44.39 c d 7.48 15 69.88 d d 12.47 45.52 c d 8.24 Finger-nose- 12 75.71 a a 2.87 74.81 e 2.39 finger 13 70.28 a 6.26 67.52 a d e f 5.76 14 71.27 a b c 5.79 72.94 f 5.33 15 74.00 c d 2.73 12 72.76 7.88 62.65 8.79 13 79.62 10.53 64.74 9.32 14 82.44 10.61 66.67 10.43 15 86.87 10.89 66.20 9.25 12 37.87 2.62 37.03 2.82 13 37.55 2.74 34.65 3.59 14 37.61 2.40 36.45 3.20 15 37.56 3.39 33.88 2.93 12 95.20 16.35 93.22 21.52 13 95.60 17.71 100.74 17.52 14 95.20 17.58 99.37 19.34 15 94.88 16.92 106.88 16.30 Grip strength Jumping Heel-toe Balance 66.36 a ef cd 6.69 Note. ns, B12 = 55, B13 = 53, B14 = 41, B15 = 16, G12 = 37, G13 = 54, G14 = 49, G15 = 25. Same superscript letters indicate significant differences within group pairwise comparisons. Same subscript letters indicate significant differences between group pairwise comparisons. Bolded letters indicate the focus for all of the comparisons being made (i.e.,. a = B12, b = B13, c = B14, d = B15, e = G12, f = G14). A Bonferroni correction is used for all post-hoc comparisons. 91 Table 27. ANOVA results for the MAND Gross Motor Skills. Grip strength Finger-nose-finger Jumping Heel-toe Balance Effect df F Sig. Gender 1/322 87.79 .001 Age 3/322 38.46 .001 Gender by Age 3/322 13.58 .001 Gender 1/322 15.59 .001 Age 3/322 26.58 .001 Gender by Age 3/322 8.26 .001 Gender 1/322 175.90 .001 Age 3/322 10.77 .001 Gender by Age 3/322 2.99 .031 Gender 1/322 36.49 .001 Age 3/322 5.14 .002 Gender by Age 3/322 3.57 .014 Gender 1/322 5.00 .026 Age 3/322 1.46 .226 Gender by Age 3/322 1.48 .219 Finger-Nose-Finger 70 80.00 60 75.00 Score Score Grip Strength 50 70.00 40 65.00 30 60.00 12 13 14 15 12 13 Figure 7. 15 Age (years) Age (years) Boys 14 Girls Boys Girls Significant age by gender interactions for the gross motor skills of Grip Strength and Finger-nose-finger. G13 group and G15 group (Effect sizes: 1.24 and 1.39, respectively). Comparison amongst the girl groups indicated that the G12 group performed significantly better than the G13 and 92 G15 groups (Effect sizes: 1.55 and 1.83, respectively). In addition, the G14s performed better than the G13 and G15 groups (Effect sizes: .97 and 1.13, respectively). Main Effects Jumping. There was a significant main effect of gender for the MAND jumping motor skill, F(1,322) = 175.90, p < .001. The girls performed poorer than the boys (Girls, M = 65.07 ± 9.57 and Boys, M = 78.74 ± 10.77; Effect size: 1.34; 95% CI 63.59 – 66.54 and 77.08 – 80.40, respectively). There was also a main effect for age, F(3,322) = 10.77, p < .001. Post-hoc analysis revealed that the 12-year-olds performed the jumping motor skill significantly poorer than the 14-year-olds (Effect size: .45) (see Table 28). Heel-toe-heel. There was a significant main effect of gender for the MAND motor skill heel-toe-heel, F(1,322) = 36.49, p < .001. The boys performed better than the girls (Girls, M = 35.60 ± 3.41 and Boys, M = 37.67 ± 2.67; Effect size: .68; 95% CI 35.08 – 36.12 and 37.26 – 38.08, respectively). Table 28. Jumping Descriptives for the Main Effect Age on the Jumping Motor Skill. n Age Mean SD CI 92 12 68.69# 9.60 66.71 – 70.68 107 13 72.11 12.40 69.74 – 74.49 90 14 73.86# 13.10 71.11 – 76.60 41 15 74.27 14.14 69.80 – 78.73 Note. *, denotes significant difference found between the 12- and 14-year-olds. CI = 95% Confidence Interval. 5.3. BALANCE AND MOVEMENT COORDINATION (BMC) INSTRUMENT The BMC instrument records information regarding body balance (3 motor skills) and movement coordination (6 motor skills). The body balance skills include two static balance tests - balancing on one-foot with eyes open and balancing on one-foot with eyes closed. The final balance test is a dynamic balance test involving performing sidesteps with the legs together while jumping sideways. The movement coordination skill tests involve a shuttle run without an object, hopping in a square, hopping with speed, a shuttle run with an object, a zigzag run, and a quadrant jump exercise. The reliability of the BMC, gender and age 93 differences in the BMC tests among Malaysian adolescents were addressed by dividing the results into: i. Reliability of the BMC motor skill instrument, ii. body balance items, and iii. movement coordination items. 5.3.1. Reliability of the BMC Motor Skill Instrument Initially, analyses of two BMC item scores obtained from two testing sessions were examined for the reliability of each item and overall items. Thirty-three participants aged 13 years (20 boys, 13 girls) participated in both sessions. Table 29 presents means and standard deviations for BMC test items on the two testing sessions, the reliability scores for each of the BMC items, and the overall reliability score of the BMC tests. Results showed that the shuttle run with and without object, zigzag run and hopping speed tests recorded the highest reliability scores (r = .97 - .99) while the quadrant jump test was the lowest (r = .70). The average r across all measures was 0.88. The high individual and average BMC test scores indicated that test items were reliable and acceptable for further testing. Table 29. Means ± SDs and Reliability Coefficients for the BMC. Testing session First Second Variables Mean SD Mean SD r One-foot balance with eyes open (s) 110.82 21.62 108.42 19.27 .88 One-foot balance with eyes closed (s) 49.82 30.36 65.52 29.66 .81 Dynamic balance (number of jumps ) 19.48 5.39 20.27 5.29 .84 Hopping-in-square (number of hops) 45.73 7.78 47.15 7.58 .84 Hopping speed (s) 11.03 2.91 11.17 2.78 .99 Zigzag run (s ) 13.09 1.36 13.17 1.38 .98 Shuttle run with object (s) 10.65 1.44 10.78 1.53 .97 Shuttle run without object (s) 10.55 1.44 10.56 1.47 .99 Quadrant jump (total score) 27.73 5.77 29.53 7.35 .70 94 5.3.2. Body Balance Motor Skills Descriptives The means and standard deviations of body balance items of the BMC can be found in Table 30. For the One-foot-eyes open task the mean time for the girl groups increased with age, and the boys performances varied across age groups. The mean times for the girl groups also increased with age for the One-foot balance with eyes closed. However, the boys’ mean balance times decreased with age. Finally, Dynamic balance of the boys was more stable than that found for the girls. ANOVAs A main effect for gender was found for the dynamic balance motor skill (p < .001)(see Table 31). No other significant differences were noted between the other groups or within each gender age groups. Table 30. Means ± SDs for the BMC Body Balance Motor Skills. Age Boys Girls Variables (years) Mean SD Mean SD One-foot 12 117.05 10.96 108.30 20.64 balance 13 114.51 17.78 111.37 15.99 with eyes open 14 113.10 14.95 112.00 14.63 (sec.) 15 117.63 6.72 117.00 7.97 One-foot 12 52.00 28.03 48.97 34.46 Balance with 13 51.25 30.66 57.02 36.14 eyes closed 14 53.05 33.71 60.51 32.92 (sec.) 15 48.63 32.46 67.24 34.27 Dynamic 12 20.11 3.68 19.19 3.94 balance 13 22.72 3.77 20.15 5.38 (jumps) 14 22.98 5.76 17.90 5.16 15 22.69 2.80 22.36 4.31 Note. ns, B12 = 55, B13 = 53, B14 = 41, B15 = 16, G12 = 37, G13 = 54, G14 = 49, G15 = 25. 95 Table 31. ANOVA Results for the BMC Body Balance Motor Skills. Univariate ANOVA Variables Effect df F Sig. One-foot balance Gender 1/322 3.547 .061 with eyes open Age 3/322 1.065 .364 Gender by Age 3/322 1.197 .311 One-foot balance Gender 1/322 3.375 .067 with eyes closed Age 3/322 .733 .533 Gender by Age 3/322 1.050 .371 Gender 1/322 16.46 .001 Age 3/322 4.59 .004 Gender by Age 3/322 3.98 .008 Dynamic balance A simple effect analysis on dynamic balance indicated that the girls dynamic balance time was significantly less compared to the boys (Girls, M = 19.60 ± 5.04 and Boys, M = 21.91 ± 4.41; Effect size: .49; 95% CI 18.82 – 20.38 and 21.83 – 22.59, respectively). 5.3.3. Movement Coordination Motor Skills Descriptives Results indicated that the mean times of 12-14 year old boys for the Shuttle run without object were better than the girls’ groups. However, the 15 year old girls were slightly better than the boys (see Table 32). Boys outscored the girls at Hopping-in-square except at age 15 years, where G15 performed the greatest number of hops. Hopping speed times tended to improve with age for boys but the reverse tended to occur with girls. The boys’ mean times for the Shuttle run with object were better than the girls, but the girls’ times did tend to improve with age. Both boys and girls recorded similar times for the Zigzag run and that their performances were similar across the age groups. The mean number of Quadrant jumps for the girls increased with age, and that from age 13 the girls outperformed the boys. The boys’ performances were varied across their age groups. 96 Table 32. Means ± SDs for the BMC Movement Coordination Motor Skills. Age Boys Girls (years) Mean SD Mean SD Shuttle run 12 10.04 .85 11.02 1.05 Without 13 9.76 .82 10.97 1.12 Object (secs) 14 9.92 .79 10.97 1.14 15 10.60 1.43 10.26 .97 Hopping-in- 12 49.75 9.23 45.59 6.09 Square (jumps) 13 49.33 9.60 46.57 11.03 14 48.61 13.04 44.76 8.23 15 46.19 11.95 50.64 6.77 Hopping speed 12 9.34 a 1.68 10.79 a 3.04 (secs) 13 9.48 1.49 10.74 2.65 14 10.32 1.70 10.17 2.96 15 10.72 2.59 9.14 2.04 Shuttle run with 12 10.18 .82 11.86 1.48 object (secs) 13 9.83 .82 11.49 1.32 14 9.99 .79 11.43 1.33 15 10.76 1.50 11.05 1.21 12 13.07 1.38 13.15 1.72 13 12.11 1.53 13.12 1.25 14 12.94 1.28 13.29 1.53 15 13.78 1.17 13.02 1.43 Quadrant jump 12 25.65 5.62 26.55 8.02 (jumps) 13 28.65 6.75 29.17 6.69 14 26.35 5.54 31.30 7.89 15 25.69 6.20 32.70 6.73 Zigzag run (secs) Note. ns, B12 = 55, B13 = 53, B14 = 41, B15 = 16, G12 = 37, G13 = 54, G14 = 49, G15 = 25. Same superscript letters indicate significant differences within group pairwise comparisons. Same subscript letters indicate significant differences between group pairwise comparisons. Bolded letters indicate the focus for all of the comparisons being made (i.e., a = B12). A Bonferroni correction is used for all post-hoc comparisons. 97 Table 33. ANOVA Results for the BMC Movement Coordination Motor Skills. Effect df F Sig. Shuttle run without Gender 1/322 35.84 .001 Object Age 3/322 .72 .544 Gender by Age 3/322 4.92 .002 Gender 1/322 1.83 .178 Age 3/322 .40 .751 Gender by Age 3/322 2.02 .111 Gender 1/322 .76 .384 Age 3/322 .19 .901 Gender by Age 3/322 5.44 .001 Shuttle run with Gender 1/322 90.21 .001 object Age 3/322 1.72 .164 Gender by Age 3/322 3.82 .010 Gender 1/322 .94 .334 Age 3/322 3.96 .009 Gender by Age 3/322 4.08 .007 Gender 1/322 17.11 .001 Age 3/322 3.78 .011 Gender by Age 3/322 3.61 .014 Hopping-in-square Hopping speed Zigzag Run Quadrant Jump ANOVAs Results from univariate ANOVAs (see Table 33) revealed a significant gender by age interaction for Hopping speed (p < .001). Significant main effects for gender were found for the two Shuttle run motor skill tests and for the Quadrant Jump (ps < .001). Interactions. Hopping Speed. The simple effect analysis indicated that the B12s differed significantly from the G12 group (Effect size: 62). No other significant performance differences were evident between the boy and girl groups. In addition, no significant performance differences were found amongst the boy groups or amongst the girl groups. Figure 8 illustrates the significant age by gender interaction for the Hopping speed motor skill. 98 Seconds Hopping Speed 11 10.5 10 9.5 9 8.5 8 12 13 14 15 Age (years) Boys Figure 8. Girls Significant age by gender interaction for the Hopping speed motor skill. Main Effects. Shuttle Run without Object. The simple effect analysis on the Shuttle run without object times showed that the boys time was significantly quicker than the girls time (Girls, M = 10.91 ± 1.13 and Boys, M = 9.87 ± 1.31; Effect size: .85; 95% CI 10.74 – 11.09 and 9.67 – 10.07, respectively). Shuttle Run with Object. The subsequent simple effect analysis showed that the boys time was significantly quicker than the girls time (Girls, M = 11.52 ± 1.35 and Boys, M = 10.08 ± .92; Effect size: 1.25; 95% CI 11.31 – 11.73 and 9.94 – 10.22, respectively). Quadrant Jump. The simple effect analysis of the quadrant jump showed that the boys number of jumps were significantly less to that reported by the girls (Girls, M = 29.75 ± 7.61 and Boys, M = 26.79 ± 6.13; Effect size: .43; 95% CI 28.57 – 30.91 and 25.85 – 27.73, respectively) 99 5.4. DISCUSSION 5.4.1. Performance on the AIS – Anthropometric Data Improvement of motor ability varies with gender and age groups during adolescence (Bloomfield, Blanksby & Ackland, 1990; Espenschade, 1940; Kim et al., 1999; Little et al., 1997; Loko et al., 2000, 2003; Malina, 1978; Thomas & French, 1985; Tomkinson et al., 2003; Viru et al., 1998; Volver & Selge, 1997; Volver et al., 2000). Thus, height, body mass and BMI portrays subjects’ physiques as motor ability performances are correlated with chronological age in adolescents (Viru et al., 1998; Volver & Selge, 1997; Volver et al., 2000). Table 34 illustrates the means and standard deviations of heights and weights from the data in this study, and those previously collected by the Malaysian Sports Council (Majlis Sukan Negara, 1998). The pattern for heights and weights across age tends to parallel that of Australian adolescents from both genders (Tomkinson et al., 2003). These results also parallel those reported for Estonian girls (Loko, Aule, Sikkut, Ereline & Viru, 2000; Loko et al., 2003; Volver & Selge, 1997; Volver et al., 2000), and Japanese, Chinese, Hong Kong and Taiwanese girls (Kim et al., 1999). Table 34. Mean Heights and Weights ± SDs of the Malaysian Sports Council Data and the Current Research. Malaysian Sports Council Data Boys Participants in this Study Girls Boys Girls Age Mean SD Mean SD Mean SD Mean SD Height 11 146.5 9.9 147.8 7.83 - - - - (cm) 12 146.54 9.40 148.4 7.78 148.3 8.34 150.2 6.4 13 153.81 9.90 151.85 7.13 154.8 9.41 153.4 6.7 14 161.22 9.15 155.44 6.50 160.3 8.55 155.6 5.1 15 - - - - 165.1 6.63 156.4 6.6 Weight 11 39.8 10.32 39.7 8.57 - - - - (kg) 12 39.64 10.26 40.88 9.47 39.96 10.09 45.78 13.70 13 43.67 10.34 42.96 8.61 46.60 14.14 46.20 13.99 14 49.41 10.93 45.37 8.14 47.17 11.36 48.53 9.95 15 - - - - 59.06 18.01 51.58 11.70 100 The 12-15 year old Malaysian adolescents scored lower absolute percentile scores for height and weight when compared with Australian adolescents (Australian Sports Commission, 1998) (See Figures 9 and 10). Boys aged 12-14 years and girls aged 13-14 years recorded lower mean BMIs than Australian adolescents; but the mean BMI scores for 15 year old boys and girls, and 12 year old girls in this study, were larger than their Australian counterparts (Tomkinson et al., 2003). The mean BMIs among 13 and 15 year old Malaysian girls were slightly higher than Korean girls (Kim et al., 1999). However, despite some higher and lower BMIs when compared with other populations, the Malaysians scored between the 5th and 85th percentiles, thereby demonstrating a healthy weight status (de Onis, Onyango, Borghi, Siyam, Nishida & Siekmann, 2007; Pon Lai Wan, Kandiah & Mohd Nasir Mohd Taib, 2004). 101 Height - 12 year olds Height - 13 year olds 170 180 170 160 cm cm 160 150 150 140 140 130 130 0 20 40 60 80 0 100 20 AB MG MB 100 MB Height - 15 year olds 180 180 170 170 cm cm 80 MG AB AG Height - 14 year olds 160 150 160 150 140 140 0 20 40 60 80 100 0 percentile AG Figure 9. 60 percentile percentile AG 40 AB MG 20 40 60 80 100 percentile MB AG AB MG MB The percentile patterns of height among Australian adolescents (Australian Sports Commission, 1998) and Malaysian participants in this study (AG = Australian girls, AB = Australian Boys, MG = Malaysian Girls, MB = Malaysian Boys). 102 Weight -12 year olds Weight - 13 year olds 70 60 60 50 50 kg kg 70 40 40 30 30 20 20 0 20 40 60 80 100 0 20 percentile AB AG 60 80 100 percentile MG MB AG Weight - 14 year olds AB MG MB Weight - 15 year olds 80 90 70 80 70 kg 60 kg 40 50 60 50 40 40 30 30 20 20 0 20 40 60 80 100 0 20 percentile AG Figure 10. AB MG 40 60 80 100 percentile MB AG AB MG MB The percentile patterns of weight among Australian adolescents (Australian Sports Commission, 1998) and Malaysian participants in this study (AG = Australian girls, AB = Australian Boys, MG = Malaysian Girls, MB = Malaysian Boys). 5.4.2. Performance on the AIS – Motor Performance Data At all ages, the boys performed better than the girls in basketball throw, vertical jump and the 40m sprint motor skills. To help further compare the Malaysian subjects’ scores in the AIS tests with Australian norms, percentile scores were developed. The performance patterns for the Malaysian sample on vertical jump and 40m sprint increased across age and gender in a similar fashion to that reported for their same-aged Australian adolescent 103 counterparts (Australian Sports Commission, 1994; Australian Sports Commission, 1998; Majlis Sukan Negara, 1998; Tomkinson et al., 2003). However, normative values on the four other items from the AIS battery were lower for the 12-15 year Malaysians than the Australian norms (Australian Sports Commission, 1998). Graphical percentile comparisons of participants in this study and the AIS norms (Australian Sports Commission, 1998) are shown in Figures 11, 12, 13 and 14. It is probable that the lower normative scores of the AIS tests among Malaysian adolescents in this study resulted from the Malaysians being shorter and thinner than the Australian adolescents. Because somatic growth influences performance, greater height and weight provide greater strength, speed and endurance as was shown by Australian adolescents relative to subjects in this study (Beunen et al., 1988; Beunen et al., 1992; Goslin & Burden, 1986; Planinsec, 2001; Thomas & French, 1985). Strength and power are related to body shape, composition and proportionality, and posture (Bloomfield et al., 1994). Moreover, height can influence performance via greater weight and biomechanical advantage (Olgun & Gurses, 1984). Also, weight and blood volume increase in line with the cube of height whereby size changes tend to produce differences in the relationships between variables such as strength, weight, power output, acceleration and work capacity (Watson, 1995). The relationships between the above components show that individuals of various sizes are better equipped for different types of activity. Percentile score comparisons indicated that Australian adolescents have physical attributes that could give a performance advantage in selective tasks. The performance differences between Australian and Malaysian adolescents demonstrated that separate Malaysian normative scores are necessary if using the AIS instrument as a mass screening test for talent identification in Malaysia. Also, further investigations of the AIS test items are essential to signify their suitability for use in Malaysia. A comparative study applied the AIS instrument to South African adolescents, and found the test battery was unsuitable when recording results from different parts of the country (du Randt, 2000; Viljoen et al., 2004). This was considered to be due to little opportunity for involvement in, or exposure to, physical activity and/or sport, and that the South African subjects came from low socio-economic (SES) conditions which might have contributed to the below average performances. The latter is possible in the present study because stratified sampling was not possible and the convenience sampling could have masked results expected perhaps from a stratified sample. Another issue is the expectation of lower scores due to smaller stature, decreased activity experiences and time in a healthy environment (e.g., Food volume and type, rest, hours of sunlight exposure). Also, the nature, validity, reliability and generality/specificity of the tests used are important. Across populations, tests of inherent 104 ‘raw talent’ components might assist in comparative studies as they are more universally applicable. Vertical jump - 12 year olds Vertical jump - 13 year olds 50 60 50 40 cm cm 40 30 30 20 20 10 10 0 20 40 60 80 100 0 20 40 percentile AB AG 60 80 100 percentile MG MB AG Vertical jump - 14 year olds AB MB MG Vertical jump - 15 year olds 60 60 50 40 40 cm cm 50 30 30 20 20 10 10 0 20 40 60 80 100 0 20 40 Figure 11. AB MG 80 100 percentile percentile AG 60 MB AG AB MG MB The percentile patterns for vertical jump results among Australian adolescents (Australian Sports Commission, 1998) and Malaysian participants in this study (AG = Australian girls, AB = Australian Boys, MG = Malaysian Girls, MB = Malaysian Boys). 105 40 m sprint - 13 year olds 12 12 11 11 10 10 seconds seconds 40 m sprint - 12 year olds 9 8 9 8 7 7 6 6 5 5 0 20 40 60 80 0 100 20 40 AG AB AG MB MG 40 m sprint - 14 year olds 80 100 AB MB MG 40 m sprint - 15 year olds 11 11 10 10 9 9 seconds seconds 60 percentile percentile 8 7 8 7 6 6 5 5 4 4 0 20 40 60 80 100 0 20 40 Figure 12. AB MG 80 100 percentile percentile AG 60 MB AG AB MG MB The percentile patterns for 40m sprint results among Australian adolescents (Australian Sports Commission, 1998) and Malaysian participants in this study (AG = Australian girls, AB = Australian Boys, MG = Malaysian Girls, MB = Malaysian Boys). 106 Multistage Fitness T est - 13 year olds Multistage Fitness T est - 12 year olds 100 100 complete laps complete laps 80 60 40 80 60 40 20 20 0 0 0 20 40 60 80 0 100 20 40 percentile AG MG AB AG MB Multistage Fitness T est - 14 year olds 80 100 AB MG MB Multistage Fitness T est - 15 year olds 100 100 80 80 complete laps complete laps 60 percentile 60 40 20 60 40 20 0 0 0 20 40 60 80 100 0 20 40 percentile AG Figure 13. AB MG 60 80 100 percentile MB AG AB MG MB The percentile patterns for the multistage fitness test results among Australian adolescents (Australian Sports Commission, 1998) and Malaysian participants in this study (AG = Australian girls, AB = Australian Boys, MG = Malaysian Girls, MB = Malaysian Boys). 107 Basketball T hrow - 13 year olds 8 10 6 8 4 6 m m Basketball T hrow - 12 year olds 4 2 2 0 5 20 40 60 80 0 95 5 percentile 20 40 60 80 95 percentile AG AB MG MB AG Basketball T hrow - 14 year olds MG AB MB Basketball T hrow - 15 year olds 10 12 8 10 8 m m 6 4 6 4 2 2 0 0 5 20 40 60 80 95 5 20 40 percentile AG Figure 14. AB 60 80 95 percentile MG MB AG AB MG MB The percentile patterns for the basketball throw results among Australian adolescents (Australian Sports Commission, 1998) and Malaysian participants in this study (AG = Australian girls, AB = Australian Boys, MG = Malaysian Girls, MB = Malaysian Boys). 108 5.4.3. Performance on the MAND Motor Skills Overall, the mean Neuro-Developmental Index (NDI) for the Malaysian sample was higher (NDI = 106.7) than that reported by McCarron (1982) among the USA normative sample (NDI = 100). Analysis across age and gender indicated that Malaysian boys aged 12-15 years, and girls aged 12-14 years scored above the mean, but girls aged 15 years scored below the USA, NDI mean score. The 13-year-old boys scored the highest NDI among Malaysian adolescents. Fine motor task scores showed that all participants, except B15, performed better than the normative scores from the USA. In general the findings indicated that participants’ superior performances in fine motor tasks provided the advantage which enabled the Malaysian scores to be greater than the USA mean on the overall score of NDI, when compared with the gross motor tasks alone. The reasons for good performances in the fine motor tasks were not examined and need further study. Perhaps the need for Malaysian subjects to help with household tasks during childhood indirectly improved their fine motor skills. Most participants were from average socioeconomic levels (farmers, rubber tappers, palm oil plantation workers, factory workers and government servants) where girls did household activities when the parents were out at work, and the boys assisted parents on a farm or rubber/palm oil plantation. Within the Malaysian sample the females outperformed the boys for beads-in-box and beads-on-rod. It is possible that the girls experience in household chores provided them with an advantage over the boys for these two fine motor skills. Additionally, the 13-year-olds significantly outperformed the 12- and 14-year-olds in finger tapping. It is not apparent as to why this finding came about. Malaysian boys scored around the same as, and girls scored less than the USA average on the gross motor tasks. The mean gross motor average score among girls for each age group was below the USA norm. The largest variation was found for Malaysian G15 which was 15 points lower than the USA norm average. An examination of individual gross motor items indicated that, generally, boys aged 12-15 years scored between low and average values of 8-10 less than scaled scores of USA norms on the two gross motor items (grip strength and jumping task). However, Malaysian girls from the same age groups scored below average by less than 5-8 than scaled scores of USA norms on the same two gross motor items. Scale score differences were minimal for the other three gross motor tasks. The below average scores by Malaysian girls, when compared with USA norms, suggested that different norm scores for the grip strength and jumping tasks, relative to gender and age, are essential for Malaysian adolescents. 109 The scale scores also indicated that the boys already showed a large range of scale scores (score = 11) which differed from girls (score = 7) as early as 12 years old on the jumping task; and 13 year olds on the hand strength task (scale score, boys = 9; girls = 7). However, the table of scale scores of MAND test norms only provided separate scale scores of the grip strength and jumping task between genders, and was for 14-18 year olds and young adults. A previous study on accelerated improvement of explosive strength indicated that boys demonstrated peak improvements between 13 and 16 years, while peaks for girls ranged between 11 and 12 years old (Viru et al., 1998). There was a different rate and timing of acceleration in improved explosive strength (Viru et al., 1998) and a large range of scaled performances on two gross motor items found between gender in this study. Thus, a separate normative scale score across gender and age, as early as 12 years old on the jumping task and 13 years old on grip strength, appears necessary for Malaysian adolescents. Only then can accurate evaluations be derived for individual motor ability performances when using the MAND test. Finally, within the Malaysian sample the male and female adolescents had varied performances on the gross motor skills grip strength and finger-nose-finger. For the grip strength task for both boys and girls their strength increased, with this increase being far greater for the boys. It is possible that simple maturation factors in boys can account for this difference. For the finger-nose-finger task the boys generally outperformed the girls. It is not apparent as to why this finding came about. The boys were also superior in their jumping and heel-toe performances compared to the girls. Finally, 14-year-olds significantly outjumped the 12-year olds. It is possible that for the jumping performances simple maturation factors in the boys and for age can account for these differences. With regards to the heel-toe performances it is not apparent as to why this finding came about. 5.4.4. Performance on the BMC Motor Skills For the motor skills assessing body balance, only performance on the Dynamic Balance was found to show significant differences. In general the boys performed this motor better than the girls. The two movement coordination motor skills of the Shuttle Run and the Shuttle Run with Object revealed that the boys outperformed the girls. An examination of Hopping Speed revealed that despite outperforming the girls at age 12 the boys performance deteriorated with an increase in age while the girls improved their perfromance the older they got. 110 Finally, the results for the Quadrant Jump indicated that the number of correct jumps for the girls increased with age and that from age 13 the girls outperformed the boys. Overall, the younger boys of 12-13 years old performed better in the dynamic balance, shuttle-run-without-object, shuttle-run-with-object, quadrant jump when compared with girls of the same ages. However, the 15 year old girls performed better in hopping speed and quadrant jump than boys at the same age. The reason for the better performances on these two motor skills shown by G15 is unclear. The lower BMI of girls could be due to being thinner than the boys and it was easier for them to project and absorb body weight, produce minimal contact duration and maintain balance required for hopping and quadrant jumps. 5.5. SUMMARY Malaysia has a unique culture and social system via three major ethnic groups, Malay, Chinese and Indians, who live together harmoniously. In the educational system, physical education (PE) classes are conducted in same-gender groups and are preferably conducted by a teacher of the same gender. As students wear uniforms to school, they need to change into suitable PE attire for class. Also, the Malaysian education system places much emphasis on academic examination performances, from which PE is excluded. Hence, the focus and participation in PE classes is less valued and sometimes neglected. Therefore, a description of motor ability performances is important to illustrate the performance levels among Malaysian adolescents. Overall, Malaysian adolescents in this study demonstrated lower absolute performances in comparison to other populations in MAND and AIS tests. This might be due to lack of largescale public health/education promotion on the importance of motor ability, fitness and sport for Malaysian children, adolescents and adults; and they are not motivated into exercise and sport. The lower motor abilities among girls could be influenced by socio-cultural factors in Malaysian society, which usually draws them into domestic tasks rather than vigorous participation in sports. The resultant limited sporting opportunities would reduce the chances for girls to explore and excel in the motor ability performances required in elite sport. The wide range in variability of motor task scores across gender and age in this study was comparable with previous results (Branta et al., 1984; Espenschade, 1940; Malina, 1978; Thomas & French, 1985). Evidence indicates that performance changes are influenced by somatic growth and maturation (Beunen et al., 1988; Beunen et al., 1992; Planinsec, 2001; Thomas & French, 1985); environment (Birrer & Levine, 1987; Malina, 1978; Thomas & 111 French, 1985); social, cognitive and other personal factors (Sallis & Hovell, 1990). Generally, these factors have contributed to better performances among boys (Nelson et al., 1986; Thomas, 2000; Thomas & French, 1985) than girls (Little et al., 1997; Nelson et al., 1986; Thomas, 2000), as occurred in this study. It can be concluded that physical growth, maturation, environment and social factors do influence the motor ability performance of Malaysian adolescents as measured by the AIS, MAND and BMC. The above average scores on the NDI of MAND tests, based on USA norms, suggests a need to develop normative data for the MAND test specific to Malaysian adolescents. It is possible that the greater manual requirements of Malaysian living provide an advantage in this domain. Norms are based upon the status quo, as gender and age factors influence performance on several items of gross motor tasks, as shown in this study. Different norm scores which are specific to gender and age are essential from as early as 12 years old. In the MAND test, the norm scores are specific to gender and age, but were started only at the age of 14 for grip strength and jumping. The development of such norms would reflect the present condition of the Malaysian population. This chapter has provided descriptive information on 330 Malaysian adolescents on the AIS, MAND and BMC motor skill test batteries. The results presented here could be used in establishing norms for Malaysian age groups, albeit limited to a relatively small sample size (N = 330), and 12-15 year old subjects not randomly selected. Then, it could provide a baseline of information for identifying athletic talent because, overall, the tests detected both gender and age differences in performance. They incorporated recognised basic TI measures via the AIS instrument; and also included fine motor, gross motor, balance and movement coordination skill tests via the MAND and BMC. The inclusion of the MAND and BMC with the AIS for TI among Malaysians was due to suggestions made that the AIS on its own may inappropriate for use with populations in cultures markedly different to that found in Australia. Thus, the broader nature of the MAND and BMC were hoped to tap into the motor skills relevant to Malaysians. This study suggested that they did but not sufficiently so to demonstrate that they will help TI in Malaysia. To examine this further, one needs to find whether the tests can reliably discriminate between individuals. Hence, the discriminatory ability of a motor skill instrument made up of the combined AIS+BMC motor skills was explored in two ways i) to classify the adolescents into three motor coordination groups derived by the MAND, and ii) to classify the adolescents into three motor ability groups derived from a framework out of the current research. This framework is GMA. 112 CHAPTER 6 DISCRIMINANT ANALYSIS OF THE COMBINED AIS+BMC MOTOR SKILL SET A combined AIS+BMC motor skill set underwent discriminant analysis to find a reduced set of motor skills that could reliably discriminate between the three motor ability groups. The groups were derived firstly from the MAND which is a valid and reliable diagnostic tool for neuromuscular development (McCarron, 1982). Although the MAND is best suited to a basic level recognition of motor problems within individuals, it was considered to be a good basic assessment of motor coordination. McCarron (1982) provided standardised measurements with cut-off values for different levels of disability; based on a distribution with a mean of 100 and a standard deviation of 15. This was because McCarron considered that disability begins 1 standard deviation below the mean. However, the top end of the distribution was also of key interest in the current study. Thus, participants falling 1 standard deviation below the mean were considered poorly coordinated, and those between 1 standard deviation below or above the mean were considered normally coordinated. Finally, those participants greater than1 standard deviation above the mean were considered to have high levels of motor coordination. Because the MAND best recognised the motor problems end of the skill continuum, attention was directed to a framework considered more applicable to sport. This framework was derived from the pairing of the AIS and BMC motor skill instruments used to test for a ‘g’ in motor ability. Specifically, individual factor scores from the higher-order factor analysis testing a motoric ‘g’ were identified for each participant. Based on a distribution with a mean of 0 and a standard deviation of 1, the participants were then categorised into three groups of motor ability, similar the procedure as described above for the MAND. 6.1. GROUP CLASSIFICATION BASED ON SCORES ON THE MAND Using the Neuromuscular Development Index (NDI) scores derived from the MAND, the participants were initially classified into three groups of motor coordination – poor motor coordination, normal motor coordination and high motor coordination. The NDI is a general measure of the MAND motor skills or a motor quotient and is comparable to IQ (McCarron, 1982). Subsequently, the NDI is based on a distribution where the Mean is 100 and the Standard Deviation is 15. Within McCarron’s (1982) framework, scores falling more than 113 one standard deviation from the mean are considered not normal. The current research also adopted this approach. Thus, participants with an NDI score < 85 for the MAND were categorised as poor; those participants with an NDI score from 85 to 115 were classified as normal, and those participants with an NDI score > 115 were classified as high. The number of participants and percentages classified according to gender, age and level of coordination are presented in Table 31. As seen in Table 35, 10 participants were dropped from the original 330 subjects due to missing data. The missing data appeared to be randomly scattered throughout the groups and predictors. Additionally, some of the cells were too small for discriminant analysis. Hair et al. (1998) recommended a minimum of 20 cases per group for analysis purposes, and for the adolescent boys an n = 7 was unacceptable. This left a sample of 320 for analysis purposes (29 - poor coordination, 223 - normal coordination, and 68 - high coordination). Table 35. Number and Percentage of Participants in the Three Motor Coordination Groups. Age (years) Poor Normal High Boys Girls Boys Girls Boys Girls Total % 12 3 - 35 31 16 6 91 28.44 13 1 8 31 41 18 5 104 32.50 14 3 7 27 26 9 13 85 26.56 15 - 7 15 17 1 - 40 12.50 TOTAL 7 22 108 115 44 24 320 100 Statistical analyses Stepwise estimation was used to derive the discriminant function. This type of analytic approach reveals the best set of motor skills that can discriminate between the three groups. Then, the discriminant functions were examined to note any motor skills of importance that, due to collinearity issues, were not present in the stepwise findings. A potency index was also calculated to indicate the relative importance of a motor skill to the discriminant function (Hair et al., 1998). The fit of the discriminant analysis was then assessed using a jackknife classification using prior probabilities to account for the unequal sizes of the groups. The jackknife classification procedure was employed because the sample was unable to be split to allow for cross validation of the discriminant findings. The jackknife 114 classification procedure estimates the discriminant model by leaving out one observation and then predicting that case with the estimated model. As this is done in turn for each observation, thus, that observation never influences the discriminant model that predicts its classification (Hair et al., 1998). Hence, jackknifed classification gives a more realistic estimate of predictors with the ability to separate the groups (Tabachnick & Fidell, 2007). Finally, an examination of the adolescents who were misclassified was undertaken to understand the nature of these individuals. For the misclassification examination, the standard predicted membership was based on the standard classification procedure, not the jackknife procedure. Thus, the misclassified groups’ n may differ from that reported for the jackknife classification procedure. It was intended to to perform discriminant analysis separately on the boys and the girls. However, owing to the Poor coordination group of the boys failing to meet the recommended minimum 20 cases per group (Hair et al., 1998), only the full sample results are presented here. To remove the possible confounding effect of chronological age and gender differences, the raw scores of the AIS and BMC motor skills were standardised within-gender-by-age classification. They were then transformed into T-scores based on means and standard deviations, for each gender and age group. These normalised T-scores then were used in the discriminant analysis. To see the results of a discriminant analysis performed separately on the adolescent girls please refer to APPENDIX J on the CD. 6.2. RESULTS – ALL PARTICIPANTS The results of the stepwise estimation revealed six motor skills that could discriminate between the three groups. Specifically, the Shuttle-Run-With-Object entered on the first step Wilks Lambda = .71, F(2, 317) = 63.83, p < .001, the Balance-Eyes-Open test on the second step Wilks Lambda = .65, F(4, 632) = 37.67, p < .001, the Basketball Throw test on the third step Wilks Lambda = .60, F(6, 630) = 30.60, p < .001, the Balance-Eyes-Closed test on the fourth step Wilks Lambda = .57, F(8, 628) = 25.22, p < .001, the Hopping Speed test on the fifth step Wilks Lambda = .55, F(10, 626) = 21.68, p < .001, and the Dynamic Balance test on the sixth step Wilks Lambda = .54, F(12, 624) = 18.96, p < .001. Two canonical discriminant functions were computed for the AIS+BMC (see Table 36). Specifically, the first function produced a Wilks Lambda = .54, with a Chi-square (12) = 195.50, p < .001, and the second function produced a Wilks Lambda = .91, with a 115 Table 36. Standardised Weights, Structure Canonical Coefficient Values, Potency Index, Canonical Correlations, Eigenvalues and Group Centroids for the Three Motor Coordination Groups. Discriminant Function First Second SW Value PI SW Value PI Shuttle Run With Object .53 .76 .50 -.32 -.22 .01 Shuttle Run NI .71 .44 NI -.11 .00 Hopping Speed .35 .67 .39 -.12 -.03 .00 Zigzag Run NI .51 .23 NI .04 .00 Basketball Throw .41 .49 .21 -.19 -.17 .00 Balance Eyes Closed .31 .44 .17 .15 .36 .02 40m Sprint NI .43 .16 NI .12 .00 Multistage Fitness Test NI .34 .10 NI .06 .00 Hopping-in-Square NI .26 .06 NI .22 .01 Quadrant Jump NI .25 .05 NI .16 .00 Vertical Jump NI .23 .05 NI .05 .00 Balance Eyes Open .13 .29 .07 .71 .77 .08 Dynamic Balance -.03 .27 .06 .56 .53 .04 Canonical Correlation .64 .30 Eigenvalue .69 .10 Group Centroids Poor -1.10 -.91 Normal -.33 .17 High 1.54 -.16 Note. SW: Standardised weights. NI: Not included in the stepwise solution. Value: Structure correlations with correlations greater than .50 in bold. PI: Potency Index. Chi-square (5) = 30.23, p < .001. The canonical R2s for the two functions were .41 for the first function and .09 for the second function. The two discriminant functions accounted for about 87% and about 13%, respectively, of the between-group variability. An examination 116 of the unstandardised canonical discriminant functions evaluated at group means reveals that the first function maximally separates the Highly coordinated group from both the Normal and Poorly coordinated groups. The second function discriminates between the Normal group and the Poor group with the High group in between. An examination of the structure correlations for the discriminant analysis revealed that two motor skills not reported in the stepwise estimation - the shuttle run and the zigzag run appeared to have a substantial effect on discriminating between the three coordination groups. Thus, for the first discriminant function, the structure correlations suggest that the best motor skills for discriminating between the high motor coordination group and the other two motor coordination groups are: Shuttle-Run-with-Object, Shuttle Run, Hopping Speed and Zigzag Run. The means for these motor skills revealed that the High group recorded better performances than either the Normal or Poor coordination groups: Shuttle-Run-withObject (Mean = 9.58, SD = .97 vs Mean = 11.06, SD = 1.27 and Mean = 11.59, SD = 1.17, respectively), the Shuttle Run (Mean = 9.40, SD = .97 vs Mean = 10.57, SD = 1.33 and Mean = 11.27, SD = 1.07, respectively), the Hopping Speed (Mean = 8.11, SD = 1.01 vs Mean = 10.46, SD = 2.23 and Mean = 11.36, SD = 3.01, respectively), and the Zigzag Run (Mean = 11.81, SD = .88 vs Mean = 13.24, SD = 1.43 and Mean = 13.72, SD = 1.50, respectively). The discriminatory power of these tests appears to be relatively good given their respective potency indices. In the second discriminant function, the best motor skills for discriminating the Normal coordination group from the other two coordination groups were: Balance-Eyes-Open and Dynamic Balance. The means for these motor skills revealed that the Normal group recorded better performances than the Poor coordination group: Balance-Eyes-Open (Mean = 114.09, SD = 14.27 vs Mean = 101.10, SD = 20.43), Dynamic Balance (Mean = 20.87, SD = 4.59 vs Mean = 16.67, SD = 4.68), and recorded poorer performances than the High coordination group: Balance-Eyes-Open (Mean = 114.09, SD = 14.27 vs Mean = 118.16, SD = 10.30), and Dynamic Balance (Mean = 20.87, SD = 4.59 vs Mean = 22.18, SD = 5.06). However, according to their respective potency indices, the discriminatory power of these two motor skills is relatively low (.08 and .04, respectively). The jackknife classification procedure examined how well the motor skills could assess group membership prediction. This classification analysis revealed that 251 (78.44%) of the participants were classified correctly, when compared with 173 (53.92%) who would be correctly classified by chance alone. However, using sample proportions as prior probabilities, it appears that only the Normal coordination group were more likely to be 117 correctly classified (88.8%), with a small proportion of the Normal group being classified as either Poor (3.6%) or High (7.6%). The High coordination group reported 66.2% correct classifications, with 30.9% being classified as Normal and 2.9% as Poor. Finally, the Poor coordination group had 27.6% correct classifications, with 69% being classified as Normal, and 3.4% as High. Thus, the classification rate of around 78% was achieved, despite a disproportionate number of participants being classified as Normal. Finally, an examination of the adolescents who were misclassified revealed the following (see Table 37). Of the twenty Poor motor coordination individuals who were misclassified, 19 were misclassified as Normal. These individuals, with the exception of the two Shuttle runs and the 40m Sprint, performed the motor skills to a higher standard than their correctly classified Poor cohorts, with a significant performance improvement for Balance-Eyes-Open (p < .001). One Poor motor coordination adolescent was classified as High. This individual performed all of the motor skills to a higher standard than the correctly classified Poor cohorts. The 15 Normal motor coordination individuals who were misclassified as High were able to perform all the motor skills to a higher standard than their correctly classified Normal cohorts. Significant performance improvements were found for the Shuttle-RunWith-Object and Shuttle-Run-Without-Object, Hopping Speed, Zigzag Run, Multistage Fitness Test, Quadrant Jump and Balance-Eyes-Open (p < .001). The seven Normal motor coordination participants, who were misclassified as Poor except for the Basketball Throw test, performed all of the motor skills to a lower standard than their correctly classified Normal cohorts; but with a significant performance decrement for the Balance-Eyes-Open test (p < .002). For the 21 High motor coordination individuals who were misclassified as Normal, except for the Balance-Eyes-Open test, motor skills were performed to a lower standard than their correctly classified High cohorts. Significant performance decrements were found for the Shuttle Run-With-Object, Shuttle-Run-Without-Object, Basketball Throw and Vertical Jump (ps < .003). The two High motor coordination individuals who were misclassified as Poor, with the exception of the two Shuttle Run skills, the Zigzag Run and the Basketball Throw, motor skills were performed to a lower standard than their correctly classified High cohorts, with a significant performance decrement for the BalanceEyes-Closed (p < .002). 118 Table 37. Profiling Correctly Classified and Misclassified Observations in the ThreeGroup Discriminant Analysis for All Participants. Mean Scores Motor Group/ Correctly Motor Skills Classified Misclassified N Poor (n = 9) t test Difference t-value N H N H Sig. H# (n = 19) (n = 1) N H Shuttle Run With Object a 11.62 11.65 10.05 -0.03 1.57 .06 NA .949 NA Shuttle Run 11.53 11.13 10.30 0.40 1.23 .94 NA .358 NA Hopping Speed a 13.38 10.62 9.03 2.76 4.35 2.42 NA .023 NA Zigzag Run 14.09 13.67 10.63 0.42 3.46 .92 NA .368 NA Basketball Throw a 3.99 4.31 6.00 -0.32 -2.01 -1.19 NA .246 NA Balance Eyes Closed a 23.44 39.11 32.00 -15.67 -8.56 -2.06 NA .052 NA 40m Sprint 8.86 8.69 8.19 0.17 0.67 Multistage Fitness Test 10.89 12.68 8.00 -1.79 2.89 Hopping-in-Square 39.33 45.74 56.00 Quadrant Jump 23.00 26.45 Vertical Jump 21.56 Balance Eyes Open a Dynamic Balance a Normal NA .717 NA -1.10 NA .281 NA -6.41 -16.67 -1.53 NA .138 NA 36.50 -3.45 -13.50 -1.13 NA .269 NA 23.42 27.00 -1.86 -.61 NA .544 NA 75.22 113.00 108.00 -37.78 -32.78 -8.81 NA .001 NA 14.56 17.58 21.00 -1.64 NA .113 NA P H (n = 201) (n = 7) (n = 15) -5.44 -3.02 -6.44 P H .37 P H P H Shuttle Run With Object a 11.11 11.54 10.11 -.43 1.00 -.87 5.92 .384 .001 Shuttle Run 10.70 11.13 9.64 -.43 1.06 -1.15 6.56 .253 .001 Hopping Speed a 10.56 12.37 7.78 -1.81 2.78 -2.15 12.95 .033 .001 Zigzag Run 13.26 14.11 11.78 -.85 1.48 -1.60 4.03 .111 .001 Basketball Throw a 4.59 4.63 5.19 -.04 -.60 -.08 -3.24 .938 .004 Balance Eyes Closed a 51.29 23.43 77.07 27.86 -25.78 2.83 2.41 .018 .029 119 Table 37 continued. Motor Group/ Correctly Motor Skills Classified Misclassified Difference t-value P H P H P H Sig. P H 40m Sprint 8.23 9.00 7.35 -.77 .88 -1.61 2.72 .109 .007 Multistage Fitness Test 12.42 9.71 17.87 2.71 -5.45 1.62 4.55 .106 .001 Hopping-in-Square 47.03 41.29 54.27 5.74 -7.24 1.64 -1.92 .106 .074 Quadrant Jump 27.34 24.21 34.60 3.13 -7.26 1.28 -4.24 .200 .001 Vertical Jump 25.54 22.86 26.40 2.68 -.86 .94 Balance Eyes Open a 115.59 59.43 119.47 56.16 -3.88 5.85 -4.42 .001 .001 Dynamic Balance a 20.75 18.43 23.53 2.32 -2.78 1.37 -1.77 .173 .097 P N P N High (n = 45) (n = 2) (n = 21) P -.81 N .347 .428 P N Shuttle Run With Object a 9.26 8.74 10.37 .52 -1.11 1.17 -4.12 .248 .001 Shuttle Run 9.11 8.76 10.08 .35 -.97 1.17 -4.10 .247 .001 Hopping Speed a 7.88 8.01 8.60 -.13 -.72 -.21 -2.79 .835 .007 Zigzag Run 11.68 11.61 12.10 .07 -.42 .12 -1.78 .905 .080 Basketball Throw a 5.98 6.05 4.55 -.07 1.43 -.07 6.47 .942 .001 Balance Eyes Closed a 80.00 10.50 62.57 69.50 17.43 3.64 2.32 .001 .023 40m Sprint 7.32 8.23 7.95 -.91 -.63 Multistage Fitness Test 15.02 13.50 13.95 1.52 1.07 .40 .78 .694 .436 Hopping-in-Square 50.49 44.50 50.95 5.99 -.46 .84 -.21 .406 .834 Quadrant Jump 31.49 29.25 30.81 2.24 .68 .42 .34 .677 .734 Vertical Jump 29.36 23.50 23.43 5.86 5.93 1.28 3.68 .207 .001 Balance Eyes Open a 119.87 60.50 120.00 59.37 -.13 5.65 -.68 .111 .499 Dynamic Balance a 22.00 18.00 22.95 4.00 -.95 1.15 -.71 .254 .482 -2.00 -3.27 .051 .002 Note. a =Variables included in the stepwise estimation. P = Poor, N = Normal, H = High. NA = Not available. A Bonferroni correction adjusted the p value to 0038. Significant differences are in bold. #, raw scores presented for this individual. 120 6.3. DISCUSSION – ALL PARTICIPANTS The stepwise estimation revealed six motor skills that could maximally separate the three motor coordination groups – Shuttle-Run-with-Object, Balance-Eyes-Open, Basketball Throw, Balance-Eyes-Closed, Hopping Speed, and the Dynamic Balance. Although this is the best set of motor skills reported, the discriminant functions were also examined to find where discrimination would occur if all 13 motor skills were included in the model. An examination of the discriminant functions revealed two motor skills for further consideration – Shuttle Run and Zigzag Run. Of the two discriminant functions derived from the analysis, only the first was considered given the magnitude of the canonical structure coefficients, the potency indices and the canonical correlations. The first function indicated the motor skills that can maximally separate the High motor coordination group from the Normal and Poor coordination groups. Thus, when considering all of the motor skills as a package, the Shuttle-Run-with-Object, the Shuttle Run, Hopping Speed and Zigzag Run form the best set to separate the High motor coordination group from the other two. The mean performances of the three coordination groups on these four motor skills indicated that the High motor coordination group consistently outperformed the other two groups. Despite the second discriminant function reporting that two motor skills best discriminated the Normal motor coordination group from the other two, the function properties were too small for consideration. When assessing the fit of the discriminant model, the predictive accuracy level of the discriminant functions was examined. Using jackknife classification, the functions were reasonably able to classify the adolescents. Specifically, the hit ratio was 78%, which is considerably higher than the 54% who would be correctly classified by chance alone. The Normal group had the best correct classification hit ratio with 89% of Normals being classified correctly, with 4% classified as Poor and 7% classified as High. The High group had a correct classification hit ratio of 66%, with 31% being classified as Normal and 3% as Poor. Finally, the Poor coordination group only had a correct hit ratio of 27%. The remaining Poor motor coordination individuals were either misclassified as Normal (69%) or High (3%). What is noteworthy in these findings is the disproportionate number of cases being classified as Normal. For instance, almost a third of the High coordination group, and over two-thirds of the Poor coordination group, were misclassified as Normal. Hence, several subjects who performed the MAND motor skills quite poorly, and were subsequently categorised as Poor in basic motor coordination; were able to perform the AIS+BMC motor skills at a higher level than their correctly classified cohorts. Conversely, there were 121 individuals who performed the MAND motor skills very well and were subsequently categorised as High in basic motor coordination. But, over a third of them performed the AIS+BMC skills at a level lower than their correctly classified cohorts. Examining the misclassifications supports such a view. The Poor motor coordination individuals who were misclassified as Normal, as a group, performed the motor skills to a higher standard than their correctly classified Poor cohorts; with the exception of the two Shuttle runs and the 40m Sprint. In addition, they held the Balance-Eyes-Open motor skill significantly longer than their correctly classified Poor cohorts. The only other misclassified Poor motor coordination adolescent was classified as High. This individual performed all motor skills to a higher standard than the correctly classified Poor cohorts. The Normal motor coordination individuals who were misclassified as High, were able to perform all of the motor skills to a higher standard than their correctly classified Normal cohorts. Significant performance improvements were found for the Shuttle-Run-With and ShuttleRun-Without-Object, Hopping Speed, Zigzag Run, Multistage Fitness Test, Quadrant Jump and Balance-Eyes-Open. However, the Normal motor coordination individuals, who were misclassified as Poor with the exception of the Basketball Throw test, performed all of the motor skills to a lower standard than their correctly classified Normal cohorts; but with a significant performance decrement for the Balance-Eyes-Open. Finally, for the High motor coordination individuals, who were misclassified as Normal, except in the Balance-EyesOpen test, performed the motor skills to a lower standard than their correctly classified High cohorts. There were significant performance decrements for the Shuttle-Run-With-Object, Shuttle-Run-Without-Object, Basketball Throw and Vertical Jump. The High motor coordination individuals, who were misclassified as Poor except for the two Shuttle Run motor skills, Zigzag Run and Basketball Throw; performed the motor skills to a standard lower than their correctly classified High cohorts. However, there was a significant performance decrement for the Balance-Eyes-Closed. Thus, the misclassifications found here make sense in terms of performance. Those individuals misclassified to a level higher generally performed the AIS+BMC motor skills to a higher level than their correctly classified cohorts, and those individuals misclassified to a level lower generally performed the AIS+BMC motor skills to a lower level than their correctly classified cohorts. These findings are an important reminder about individual differences in motor skill performance and that performance in specific types of motor skills does not necessarily translate to similar levels of performance in different types of motor skills. Indeed, practitioners need to be careful about accepting performance scores at face value for a particular set of motor skills. This is especially so if these motor skills are designed for a 122 different purpose from that for which they are being used. The MAND categorised adolescents into three motor coordination groups which could be at odds with its original intention. The MAND is a valid and reliable diagnostic tool for neuromuscular development (McCarron, 1982). The motor skills within the MAND are more suited to a basic level recognition of motor problems. It was used here because it was believed that these skills also provide a good basic assessment of motor coordination, or fine and gross motor skills (McCarron, 1982). However, there were a large number of misclassifications for both the Poor and High motor coordination groups. Perhaps some individuals who did poorly on the MAND motor skills, and very well in the AIS+BMC motor skills, found the AIS+BMC skills easier to perform. Also, the MAND motor skills might not have been as stimulating to some individuals, and this reflected in their MAND performances, but not in the AIS+BMC performances. Conversely, some individuals performed the MAND motor skills to a very high standard which was not translated across to their AIS+BMC performances. The reasons for such large misclassifications in the Poor and High coordination groups remains unclear, and awaits future investigation. 6.4. GROUP CLASSIFICATION BASED ON THE MOTORIC ‘g’ From the higher-order factor analyses of the AIS+BMC for all participants, individual factor scores on the ‘g´ factor were derived. The participants were then ranked from high to low in terms of their ‘g´. Following McCarron’s (1982) method in using the standard deviation as the cut-off point for determining the groups, the participants were then categorised into three motor ability groups. Those individuals with factor scores falling 1 standard deviation below the mean were in the Low motor ability group, and individuals falling between ± one standard deviation from the mean were in the Normal motor ability group. Finally, those participants with factor scores falling 1 standard deviation above the mean were in the High motor ability group. Thus, participants who scored in the lowest 10% of ‘g’ were categorised as having Poor levels of motor ability. Participants who scored between 11% and 89% of ‘g’ were classified as having Normal levels of motor ability, and the top 10% of ‘g’ were considered to have High levels of motor ability. The same 320 participants were again used in the following discriminant analysis due to missing data (see Table 38 for the breakdown according to age and gender). The missing data appeared to be randomly scattered throughout the groups and predictors. 123 Table 38. Numbers & Percentages of Participants in the Three Motor Ability Groups. Low Age Normal High Boys Girls Boys Girls Boys Girls Total % 12 3 5 48 29 3 3 91 28.44 13 3 6 44 42 3 6 104 32.50 14 3 9 33 29 3 8 85 26.56 15 2 1 11 20 3 3 40 12.50 TOTAL 11 21 136 120 12 20 320 100 (years) It was intended to perform discriminant analysis separately on the boys and the girls. However, owing to both the Low and High motor ability groups for the boys failing to meet the recommended minimum 20 cases per group (Hair et al., 1998), only the full sample results are presented here. This left three motor ability groups for discriminant analysis (32 Low motor ability, 256 Normal motor ability and 34 High motor ability). To remove the possible confounding effect of chronological age and gender differences, the raw scores of the AIS and BMC motor skills were standardised within gender-by-age classification. They were then transformed to T-scores based on means and standard deviations, for each gender and age group. These normalised T-scores then were used in the discriminant analysis. To see the results of a discriminant analysis performed separately on the adolescent girls, refer to APPENDIX H on the CD 124 6.5. RESULTS – ALL PARTICIPANTS The results of the stepwise discriminant analysis revealed that 10 of the motor skills entered into the discriminant function. However, the Shuttle Run test that entered on the third step was subsequently removed on step 10, leaving nine motor skills for consideration. Specifically, Dynamic Balance entered on the first step Wilks Lambda = .72, F(2, 317) = 62.82, p < .001, the Balance-Eyes-Open on the second step Wilks Lambda = .57, F(4, 632) = 52.14, p < .001, the Shuttle Run on the third step Wilks Lambda = .46, F(6, 630) = 49.10, p < .001, the Quadrant Jump on the fourth step Wilks Lambda = .42, F(8,628) = 42.15, p < .001, the Hopping-in-Square on the fifth step Wilks Lambda = .39, F(10,626) = 37.80, p < .001, the Balance-Eyes-Closed on the sixth step Wilks Lambda = .37, F(12, 624) = 33.53, p < .001, the Hopping Speed on the seventh step Wilks Lambda = .35, F(14, 622) = 30.28, p < .001, the 40m Sprint on the eighth step Wilks Lambda = .34, F(16, 620) = 27.36, p < .001, the Basketball Throw on the ninth step Wilks Lambda = .33, F(18, 618) = 25.04, p < .001, the Shuttle Run was removed on the tenth step Wilks Lambda = .34, F(16, 620) = 27.71, p < .001, and the Vertical Jump entered on the eleventh step Wilks Lambda = .33, F(18, 618) = 25.31, p < .001. Two canonical discriminant functions were calculated (see Table 39). The first discriminant function produced a Wilks Lambda = .33, with a Chi-square (18) = 345.75, p < .001, and the second produced a Wilks Lambda = .89, with a Chi-square (8) = 38.24, p < .001. The canonical R2s for the two discriminant functions was .79 for the first function and .34 for the second function. The two functions accounted for about 93% and 7%, respectively, of the between-group variability. An examination of the unstandardised canonical discriminant functions evaluated at group means reveals that the first function maximally separates the High motor ability group from Poor motor ability group, with the Normal group in between. The second discriminant function maximally separates the Normal motor ability group from both the High and Poor motor ability groups. An examination of the structure correlations for the discriminant analysis did not reveal additional motor skills that had a substantial effect on discriminating between the three coordination groups beyond that indicated by the stepwise estimation. Additionally, for the first discriminant function, none of the motor skill tests exceeded the r cut-off point of .50. 125 Table 39. Standardised Weights, Structure Canonical Coefficient Values, Potency Index, Canonical Correlations, Eigenvalues and Group Centroids for the Three Motor Ability Groups. Discriminant Function First Second SW Value PI SW Value PI Dynamic Balance .31 .49 .22 -.09 .08 .00 Hopping Speed .31 .47 .20 -.35 -.16 .00 Quadrant Jump .38 .44 .18 .14 .20 .00 40m Sprint .19 .41 .16 .33 .19 .00 Hopping-in-Square .31 .40 .15 .38 .38 .01 Balance Eyes Closed .26 .36 .12 .38 .20 .00 Shuttle Run NI .35 .11 NI .04 .00 Zigzag Run NI .32 .10 NI .06 .00 Shuttle Run With Object NI .31 .09 NI .02 .00 Basketball Throw .18 .26 .06 .28 .26 .00 Vertical Jump .17 .25 .06 -.27 -.15 .00 Multistage Fitness Test NI .17 .03 NI .03 .00 Balance Eyes Open .40 .38 .13 -.77 -.69 .03 Canonical Correlation .79 .34 Eigenvalue 1.67 .13 Group Centroids Poor -3.00 .68 Normal .03 -.18 High 2.74 .76 Note. SW: Standardised weights. NI: Not included in the stepwise solution. Value: Structure correlations with correlations greater than .50 in bold. PI: Potency Index. However, the Dynamic Balance test was almost strong enough (r = .49) to discriminate the High motor ability group from both the Normal and Poor motor ability groups. An examination of the mean Dynamic Balance performances for the ability groups revealed that the High motor ability group had longer balance times (Mean = 25.69, SD = 4.34) than the 126 Normal group (Mean = 20.93, SD = 4.20) and the Poor group (Mean = 14.56, SD = 4.05). For the second discriminant function, Balance-Eyes-Open appeared to discriminate the Normal motor ability group (Mean = 115.48, SD = 11.76) from both the High (Mean = 120.00, SD = 0.00) and Poor motor ability groups (Mean = 93.94, SD = 25.48). However, the relative potency indices for the motor skills were poor for both functions. The jackknife classification analysis revealed that 293 (91.6%) of the participants were classified correctly, compared with 211.2 (66%) who would be correctly classified by chance alone. However, using sample proportions as prior probabilities, it appears that the Normal motor ability group as more likely to be correctly classified (96%) with 246 Normals classified correctly as Normal. Of the remaining 10 individuals, 5 were misclassified in the Poor motor ability group (2%) and 5 were misclassified in the High motor ability group (2%). Twenty-four of the High motor ability individuals were classified correctly (75%), with the remaining eight individuals misclassified as Normal (25%). For the Poor motor ability group, 23 were classified correctly (72%) and the remaining 9 were misclassified as Normal (18%). Thus, the classification rate of around 92% was achieved despite a disproportionate number of individuals misclassified as Normal. Finally, an examination of those adolescents who were misclassified revealed that all eight misclassified Poor motor ability adolescents were misclassified as Normal (see Table 40). With the exception of the Dynamic Balance, 40m Sprint, Shuttle Run, Shuttle-Run-withObject, Zigzag Run and the Multistage Fitness Test; the misclassified adolescents performed the motor skills to a higher standard than their correctly classified Poor ability cohorts; with a significant performance improvement for the Balance-Eyes-Open (p < .001). The three Normal motor ability individuals, who were misclassified as High except for the Shuttle Run, Shuttle Run with Object and Multistage Fitness Test; were able to perform all motor skills to a higher standard than their correctly classified Normal cohorts. But, significant performance improvements were found for the Hopping-in-Square motor skill (p < .001). The four Normal motor ability individuals, who were misclassified as Poor except for Hopping Speed, Quadrant Jump, Shuttle Run, Shuttle-Run-With-Object, Zigzag Run, Basketball Throw and Multistage Fitness Test; performed all of the motor skills to a lower standard than their correctly classified Normal cohorts. All of the misclassified High motor ability adolescents were misclassified as Normal. With the exception of Hopping Speed, 40m Sprint, Shuttle Run, Shuttle-Run-with-Object, Zigzag Run and the Multistage Fitness Test; these individuals performed the motor skills to a lower standard than their correctly classified High cohorts. 127 Table 40. Profiling Correctly Classified and Misclassified Observations in the ThreeGroup Discriminant Analysis for All Participants. Mean Scores Motor Group/ Correctly Motor Skills Classified t test Misclassified Difference t-value Sig. N H (n = 24) (n = 8) (n = 0) N H N H N H Dynamic Balance a 14.83 13.75 - 1.08 - .65 - .521 - Hopping Speed a 14.01 12.32 - 1.69 - 1.36 - .184 - Quadrant Jump a 20.52 24.25 - -3.73 - -2.05 - .049 - 40m Sprint a 9.07 9.54 - -0.47 - -1.04 - .305 - Hopping-in-Square a 38.58 39.13 - -0.54 - -.15 - .885 - Balance Eyes Closed a 27.04 27.63 - -0.58 - -.09 - .932 - Shuttle Run 11.77 12.15 - -0.37 - -.83 - .415 - Zigzag Run 14.55 14.95 - -0.40 - -.80 - .429 - Shuttle Run With Object 12.06 12.55 - -0.49 - -.83 - .415 - Basketball Throw a 4.18 4.29 - -0.11 - -.23 - .822 - Vertical Jump a 19.08 23.63 - -4.54 - -1.03 - .335 - Multistage Fitness Test 9.75 8.13 - 1.63 - 1.37 - .181 - Balance Eyes Open a 86.46 116.38 - -29.92 - -5.48 - .001 - P H (n = 249) (n = 4) (n = 3) P H P P H Dynamic Balance a 20.90 19.00 26.33 1.90 -5.43 .90 -2.23 .367 .026 Hopping Speed a 9.90 9.46 8.16 0.44 1.73 .46 1.59 .645 .112 Quadrant Jump a 27.96 28.38 37.00 -0.42 -9.04 -.13 -2.51 .893 .013 40m Sprint a 8.11 8.12 7.38 -0.01 0.73 -.01 1.10 .991 .274 Hopping-in-Square a 47.34 43.00 62.33 4.34 -15.00 Balance Eyes Closed a 54.12 19.75 81.33 34.37 -27.21 ` 5.94 -1.50 .005 .134 Shuttle Run 10.40 9.41 9.47 0.99 Poor Normal - t-value 0.93 H 1.02 -3.06 .308 .002 2.03 1.65 .043 .101 128 Table 40 continued. Motor Group/ Correctly Motor Skills Classified Misclassified Difference t-value P H P H P H Sig. P H Zigzag Run 12.92 12.64 11.71 0.29 1.21 .43 1.57 .668 .119 Shuttle Run With Object 10.75 9.45 10.95 1.30 -0.20 2.10 -.27 .037 .785 Basketball Throw a 4.73 6.35 5.87 -1.62 -1.13 -2.81 -1.70 .005 .090 Vertical Jump a 25.96 23.50 27.67 2.46 -1.71 .70 -.43 .482 .670 Multistage Fitness Test 12.93 15.00 11.33 -2.07 1.60 -.96 .64 Balance Eyes Open a 116.11 72.75 120.00 43.36 -3.89 8.17 -.65 .001 .519 P N (n = 24) (n = 0) (n = 8) P N P N P N Dynamic Balance a 26.21 - 24.13 - 2.08 - 1.18 - .246 Hopping Speed a 7.88 - 7.23 - .65 - 1.95 - .061 Quadrant Jump a 38.10 - 33.31 - 4.79 - 1.83 - .077 40m Sprint a 7.12 - 6.97 - .15 - .57 - .573 Hopping-in-Square a 60.46 - 53.88 - 6.58 - 1.69 - .101 Balance Eyes Closed a 95.08 - 74.75 - 20.33 - 1.76 - .089 Shuttle Run 9.48 - 9.30 - .19 - .61 - .544 Zigzag Run 11.49 - 11.63 - -.14 - -.37 - .716 Shuttle Run With Object 9.94 - 9.51 - .43 - 1.43 - .164 Basketball Throw a 5.73 - 5.05 - .69 - 1.38 - .177 Vertical Jump a 29.75 - 26.88 - 2.88 - 1.05 - .303 Multistage Fitness Test 17.00 - 19.25 - -2.25 - -0.88 - .387 Balance Eyes Open a 120.00 - 120.00 - 0.00 - NA - NA High Note. a =Variables included in the stepwise estimation. P = Poor, N = Normal, H = High. NA = Not available. A Bonferroni correction was used to adjust the .05 significance value to .0038. Significant differences are in bold. .340 .523 129 6.6. DISCUSSION – ALL PARTICIPANTS The stepwise estimation revealed nine motor skills that could maximally separate the three motor ability groups - Dynamic Balance, Balance-Eyes-Closed, Quadrant Jump, Hoppingin-Square, Balance-Eyes-Closed, Hopping Speed, 40m Sprint, Basketball Throw and Vertical Jump. Although this is the best set of motor skills reported, the discriminant functions were also examined to see where discrimination would occur if all 13 motor skills were included in the model. An examination of the discriminant functions did not reveal additional motor skills that had a substantial effect on discriminating between the three motor ability groups beyond that indicated by the stepwise estimation. Two discriminant functions were derived from the analysis and, given the magnitude of the canonical structure coefficients, the potency indices and the canonical correlations for both functions, the first function was deemed slightly more important than the second. The first function indicated the motor skills that can maximally separate the High coordination group from the Poor group, with the Normal group in between. However, when one considers all of the motor skills as a package, none stood out. The Dynamic Balance test was almost strong enough (r = .49) to discriminate the High motor ability group from both the Normal and Poor groups. The mean performances of the three motor ability groups on this motor skill indicated that the High ability group outperformed the other groups by exhibiting a longer balance time. The second discriminant function indicated that the best motor skill for discriminating the Normal motor ability group from the other two groups was Balance-EyesOpen. The performance mean for this motor skill revealed that the Normal group recorded better performances than the Poor ability group, and lower performances than the High motor ability group. However, according to its potency index, the discriminatory power of the Balance-Eyes-Open is low. When assessing the fit of the discriminant model, the predictive accuracy level of the discriminant functions was examined. Using jackknife classification, the functions were reasonable in their ability to classify the adolescents. Specifically, the hit ratio was 92%, which is considerably higher than the 66% who would be correctly classified by chance alone. The Normal ability group had the best correct classification hit ratio with 96% of Normals being classified correctly, with 2% misclassified as Poor and 2% misclassified as High. The High motor ability group had a correct classification hit ratio of 75%, with 25% 130 being misclassified as Normal. Finally, the Poor motor ability group had a correct hit ratio of 72%. The remaining Poor motor ability individuals were misclassified as Normal (28%). Once again, a disproportionate number of cases were classified as Normal. However, the percentages were not as high as found for the MAND framework. Using GMA scores to create the ability groups, only 25% of the High motor ability group, and 28% of the Poor motor ability group were misclassified as Normal. Thus, some adolescents who, when based on their ‘g’ scores, were classified as having Poor motor ability performed some of the AIS+BMC motor skills to a performance level higher than their correctly classified cohorts. Conversely, adolescents who, based on their ‘g’ scores, were classified as having High motor ability, performed the AIS+BMC motor skills at a performance level lower than their correctly classified cohorts. An examination of the misclassifications supports such a view. For those Poor motor ability individuals who were misclassified as Normal, with the exception of Dynamic Balance, 40m Sprint, Shuttle Run, Shuttle-Run-with-Object, Zigzag Run and Multistage Fitness Test, performed the motor skills at a higher standard than their correctly classified Poor ability cohorts. Also, they performed the Balance-Eyes-Open motor skill significantly longer than their correctly classified Poor ability cohorts. The Normal motor ability individuals who were misclassified as High; were able, with the exception of the Shuttle Run, Shuttle-Runwith-Object and Multistage Fitness Tests, to perform all of the motor skills at a higher standard than their correctly classified Normal cohorts; but with significant performance improvements for the Hopping-in-Square motor skill (p < .001). The Normal motor ability individuals who were misclassified as Poor, with the exception of the Hopping Speed, Quadrant Jump, Shuttle Run, Shuttle-Run-with-Object, Zigzag Run, Basketball Throw and Multistage Fitness Test; performed all of the motor skills at a lower standard than their correctly classified Normal cohorts. Finally, the High motor ability individuals who were misclassified as Normal, with the exception of Hopping Speed, 40m Sprint, Shuttle Run, Shuttle-Run-with-Object, Zigzag Run and Multistage Fitness Test; performed the motor skills to a lower standard than their correctly classified High cohorts. Again, it appears that the misclassifications found here make sense in terms of performance. Those misclassified to a higher level generally performed the AIS+BMC motor skills at a higher level than their correctly classified cohorts, and those misclassified to a level lower generally performed the AIS+BMC motor skills to a lower level than their correctly classified cohorts. These findings are intriguing given that the ‘g’ score was derived from the performances of the motor skills making up the AIS+BMC. The specific reasons as to why there were misclassifications for the Poor and High motor ability groups are unclear. It is possible that 131 some adolescents whose ‘g’ scores placed them in either the Poor or High ability groups did not translate those scores across to the AIS+BMC performances as derived by the discriminant functions. However, it is more likely that the best set of motor skills derived by the discriminant analysis are quite good at discriminating between the three ability groups, but fall short with particular individuals. Thus, it is important for practitioners to examine the nature of the misclassifications individually to determine the nature of these individuals. 6.7. GENERAL DISCUSSION Previous research has focused on discriminating athletes according to sport characteristics derived from physical tests (Leone et al., 2002; Proctor & Ruhling, 1981), anthropometric tests (Housh, Thorland, Johnson & Tharp, 1984a; Housh, Thorland, Johnson, Tharp & Cisar, 1984b; Housh et al., 1984c; Pienaar et al., 1998) and physiological characteristics (Smith & Thomas, 1991). Those studies showed that elite athletes have different characteristics based on the type of sport in which they are involved. However, those studies also suggest that the different characteristics of participants were further developed and influenced by intensive training. The focus of the current research was to find a reduced set of motor skills from the AIS+BMC motor skill set that could discriminate between three motor coordination/ability groups and assess classification into these groups. Initially, the MAND (McCarron, 1982) was used to derive three motor coordination groups. The MAND is a valid and reliable diagnostic tool for neuromuscular development, and the motor skills within the MAND are suited to a basic level recognition of motor problems within an individual, and believed to be a good basic assessment of basic motor coordination. Then, another approach used ‘g’ scores derived from the pairing of the AIS and BMC motor skill instruments. Specifically, individual factor scores from the higher-order factor analysis were identified for each participant, and these were used to categorise the adolescents into three motor ability groups. When utilising the MAND to categorise the adolescents, six AIS+BMC motor skills were found to maximally separate the full sample of adolescents into the MAND’s three motor coordination groups. These motor skills were Shuttle-Run-with-Object, Balance-Eyes-Open, Basketball Throw, Balance-Eyes-Closed, Hopping Speed and Dynamic Balance. The discriminant functions provided a reasonable classification hit ratio of 78%. However, the misclassifications for the High and Poor motor coordination groups were particularly high. The discriminant analysis of female adolescents revealed three AIS+BMC motor skills that maximally separated these adolescents into the MAND’s three motor coordination groups. These motor skills were Balance-Eyes-Closed, Balance-Eyes-Open and Shuttle-Run-with- 132 Object. The discriminant functions provided a reasonable classification hit ratio of 71%. However, misclassifications for High and Poor motor coordination groups were quite high. When utilising the motoric ‘g’ factor scores to categorise the adolescents, nine AIS+BMC motor skills were found to maximally separate the full sample of adolescents into the three motor ability groups. These motor skills were Dynamic Balance, Balance-Eyes-Open, Quadrant Jump, Hopping-in-Square, Balance-Eyes-Closed, Hopping Speed, 40m Sprint, Basketball Throw and Vertical Jump. The discriminant functions provided a good classification hit ratio of 92%. Thus, although the motoric ‘g’ categorisation provided better classification indices when compared with those reported for the MAND, it suggested that the sport derived categorisation procedure was more accurate. However, it may not be strictly correct to use the same 13 motor skills that created the ‘g’ scores, and then try to find the best sub-set of the same motor skills to reliably discriminate the 3 motor ability groups derived from those same ‘g’ scores. This was pursued to see if a framework grounded in sport (i.e., the AIS+BMC) would provide better separation than one grounded in disability (i.e., the MAND). The results appear to indicate this was so, but the finding needs to be treated with caution. Although not as high as with the MAND categorisation, there were still significant misclassifications for the High and Poor motor ability groups. What should be noted about the misclassifications is how extensive they were for the Poor and High motor coordination groups under the MAND framework than when compared with the GMA framework. Why this is so is unclear. Perhaps ‘g’ does not underlie all skills in the same individual. It was believed that the MAND assessed basic aspects of motor coordination and could be used to categorise the adolescents into three motor coordination groups. However, it is more probable that the MAND better assesses what it was designed to assess, namely, neuromuscular problems rather than basic motor coordination. In the current sample, the MAND appears to be assessing aspects of postural control, fine manipulative skills, and control and amplitude, rather than fine and gross motor skills. A task analysis of the MAND postural control factor suggests that it is similar to the postural control factor found for the AIS+BMC. However, the other two MAND factors of fine manipulative skills, and control and amplitude, are specifically assessing an ability to manipulate objects with the hand/s. There are no comparative motor skills within the AIS+BMC. In fact, there was little match between motor skills used to create the MAND groups and the type of motor skills used to predict group membership. However, in the ‘g’ discriminant analyses, the motor skills used to create the GMA groups were the same motor skills used to predict group membership. 133 Thus, these large discrepancies could also point to a lack of fit between the type of group (derived from the MAND) and type of motor skills being used to try and predict group membership. So, the better classification hit ratios for the ‘g’ over the MAND could just be an artefact of the positive relationship between the type of group and the types of motor skills predicting group membership. Future research needs to examine this relationship further by using the AIS+BMC to create motor ability groups; and then use motor skills not assessed by the AIS+BMC, but are similar in nature, to see how well those motor skills predict AIS+BMC group membership. The examination of the misclassifications for both sets of analyses revealed two things. In all instances where misclassification resulted in individuals being predicted to a lower group, as a group, these individuals performed a large number of the motor skills to a lesser standard than their correctly classified cohorts. Conversely, in all instances where misclassification resulted in individuals being predicted to a higher group, such individuals performed a large number of the motor skills to a higher standard than their correctly classified cohorts. The nature of these performance differences within the sub-groups indicates that, for some adolescents, their performances on specific motor skills were masked by their performances on other motor skills. Thus, at a global level, it is possible that certain individuals could be overlooked for further development. Therefore, practitioners need to be aware and cautious of a single figure of ability and how that figure might represent any individual’s athletic potential. As can be seen with the misclassified subjects, individual differences in performing specific motor skills can be masked by a single figure based on their overall performance. What was constant in these discriminant analyses was the high correct classification hit ratio for the Normal groups. Discriminant analysis is quite sensitive to sample size and larger groups have a disproportionately higher chance of classification (Hair et al., 1998). The classifications appear to support this view with the Normal group being the largest group and also recorded the highest correct classification hit ratio. However, the methodology creating the three groups was considered to be appropriate, and was able to sample the extreme ends; in particular, the top end of the distribution, using a standardised measurement approach (McCarron, 1982). Even though this would provide a large middle group, the size of the groups representing the middle and both ends of this distribution should accurately reflect findings that would be found in the normal population. It was expected that talented individuals would be more likely to exist one standard deviation above the mean in motor skill performances. Thus, this approach better reflected what naturally occurs in the general population. A proportion of the Normal population could have been selected that, in terms of 134 n, would have suited better the statistical requirements of discriminant analysis, but would not reflect the real world (Hair et al., 1998; Tabachnick & Fidell, 2007). Despite this, it should be acknowledged that the findings from the discriminant analyses seem to have some utility in identifying Normal performers given that the correct classification of the Normal groups was reasonable. The motor skills that were consistently reported in the stepwise discriminant estimations were Balance-Eyes-Open and Balance-Eyes-Closed (all four analyses), Dynamic Balance and Hopping Speed (three analyses), and Quadrant Jump, Hopping-in-Square, Basketball Throw and Shuttle-Run-with-Object (two analyses). Motor skills assessing static balance, dynamic balance and postural control are important and these findings support balance as being important in movement skill proficiency (Burton & Miller, 1998; Proctor & Ruhling, 1981). Balance is a basic motor ability in any physical circumstance (Willgoose, 1961) and is frequently included in motor ability tests (Burton & Miller, 1998). The discriminative power of balance found in this study demonstrates that balance ability is an important fundamental skill (Rarick et al., 1976). Past research has found young girls to have a slight advantage in balance tasks (Hands & Larkin, 2004; Roberton, 1984), and that boys performed moderately better after puberty (Thomas & French, 1985). Unfortunately, this was not examined due to the small cell sizes for the adolescent boys, and needs to be remedied in future research. However, the findings here seem to indicate that balance, and other qualities helpful for balance such as postural control, appear to be important discriminating components for the Malaysian adolescents. Previous research also has indicated that hopping tasks show strong discriminative power among the Poorer and Normal spectrum of coordination in children (Henderson & Sugden, 1992; Johnston, Crawford, Short, Smyth & Moller, 1987; Larkin & Revie, 1994). The hopping tasks (hopping-in-square and hopping speed) maximally separated the motor ability groups. Finally, research classifying young soccer players into elite and sub-elite groups, reported one of the best discriminative motor skills was the shuttle run (Reilly et al., 2000). The present study also recorded a similar finding in the MAND discriminant with the Shuttle-Run-with-Object motor skill. The basic findings in this study suggest that motor skills assessing balance and postural control should be included in any mass screening TI instrument for Malaysians. However, one should be mindful that the AIS+BMC only assesses the two fundamental movement skills of coordination and balance (Burton & Miller, 1998). In order to develop a more rounded mass screening instrument, motor skills assessing other fundamental movement skills need to be included. 135 In summary, the use of the stepwise estimation enabled delineation of the best set of motor skills. The discriminant functions also were able to classify the adolescents into the motor ability groups reasonably well for the MAND framework and even better for the ‘g’ framework. However, the classification indices indicated that the analyses seem to assist in identifying Normal performers rather than High performers. Unfortunately, given the number of participants and methodology employed to create these motor ability groups, the discriminant findings could not be cross-validated. Thus, if the same categorisation methodology is to be used by others, they will need to consider carefully the number of participants required for cross-validation. The results also highlight the need for practitioners to take care with how they view both individuals and groups that have been derived from a single overall performance score or rating. As found in the factor analyses, it is important to understand what the motor instrument being used is assessing in the population under study, and to bear that in mind when interpreting group performance. 136 CHAPTER 7 SUMMARY, CONCLUSIONS & RECOMMENDATIONS FOR FURTHER STUDY This research set out to examine the GMA construct and provide initial talent identification testing of Malaysian adolescents. Development of culturally specific TI assessments and normative values based on individual motor ability was deemed to be important because children from different countries have recorded different results on similar test instruments. Several countries have developed their own TI instruments and achieved excellent sporting improvements and results. However, the developmental details of these instruments are rarely published in detail. Thus, it was necessary to investigate the foundations upon which TI instruments are based for children and adolescents; as talent and skill develop mutually with motor ability and maturation. The 330 participants, aged 12-15 years, were tested on the McCarron Assessment of Neuro-Muscular Development (MAND-McCarron, 1982), the Australian Talent Identification Test (AIS - Australian Sports Commission, 1998); and a Balance and Movement Coordination Test (BMC) that was developed for the current research. 7.1. SUMMARY OF RESEARCH This project had several aims, the first of which was to identify the underlying motor abilities of the three motor skill instruments used in the current research to understand the nature of what these instruments were assessing in a Malaysian setting. Secondly, the research investigated whether a ‘g’ in motor ability could be derived from the combined AIS+BMC motor skill set of motor skills. The next aim was to examine the motor performances by 330 Malaysian adolescents on the motor skills from the three motor skill instruments employed here (i.e., the MAND, AIS and BMC motor skill instruments). Finally, an examination was undertaken to find a reduced set of motor skills from the combined AIS+BMC motor skills set that reliably discriminated and classified Malaysian adolescents into three motor ability groups. Categorisation into these motor ability groups took two forms. The first utilised performances on the MAND resulting in adolescents being categorised into Poor, Normal and High motor coordination groups. The second categorisation method utilised an individual’s ‘g’ factor score to place them into Low, Normal and High levels of motor ability. Table 41 presents a summary of the findings from the studies reported here. 137 Table 41. Summary Table of Findings. Factor Analyses Component 1 Component 2 Component 3 All Participants: ‘Postural Control’ ‘Bimanual Dexterity ‘Muscle Power MAND Heel-toe Beads on rod Grip strength Balance MAND Beads in box Finger tapping Finger-nose-finger Nut and bolt Jumping All Participants: ‘Explosive power’ AIS 40m sprint Multistage fitness test Vertical jump Basketball throw . 138 Table 41 continued. Component 1 Component 2 Component 3 All Participants: ‘Movement Coordination’ ‘Postural Control’ ‘Static Balance’ BMC Shuttle Run Dynamic Balance One-foot Balance With Shuttle Run With Object Hopping-In-Square Hopping Speed Quadrant Jump Eyes Open One-foot Balance With Eyes Closed Zigzag Run ‘g’ Higher-order Analyses Component 1 Boys: AIS+BMC Component 2 Component 3 Component 4 Higher-order Factor ‘Movement Coordination’ ‘Kinesthetic Integration’ ‘Postural Control’ ‘Explosive power’ ‘g’ Shuttle Run One-Foot Balance With Dynamic Balance Vertical Jump Quadrant Jump Basketball Throw Shuttle Run With Object Hopping Speed Zigzag Run Eyes Open Multistage Fitness Test Hopping-In-Square 139 Table 41 continued. Component 1 Girls: AIS+BMC Component 2 Component 3 Higher-order Factor ‘Movement Coordination’ ‘Postural Control’ ‘Static Balance’ ‘g’ Shuttle Run Hopping-In-Square One-foot Balance With Shuttle Run With Object Dynamic Balance 40m Sprint Basketball Throw Eyes Open One-foot Balance With Eyes Closed Hopping Speed Zigzag Run Multistage Fitness Test Vertical Jump 140 Table 41 continued. Descriptives/ANOVAs AIS MAND BMC Anthropometry Fine Motor Tests Body balance tests The boys and girls height, weight, and BMI Beads In Box: In general the girls Dynamic Balance: The jumping performance increased with age. outperformed the boys. AIS - Motor Performance Beads On Rod: The girls outperformed the Basketball Throw: In general the older boys boys. threw the basketball further than any of the groups, in particular the two eldest boy Finger Tapping: The 13-year-olds groups. outperformed the 12- and 14-year-olds. Vertical Jump: Overall the boys jumped higher than the girls. The 15-year-olds jumped higher than any oth the othe age groups. for the boys was better than the girls. 141 Table 41 continued. AIS cont. MAND cont. BMC cont. Gross Motor Tests Movement coordination tests 40m Sprint: Overall the boys were faster than the girls. Grip Strength: In general the older boys and Shuttle Run: The times for the boys were better girls increased with age. The eldest boy than the girls. group were particularly strong. Finger-nose-finger: The boys and girls had Hopping Speed: The girls improved with an varied performance across the age groups. increase in their age. The opposite trend Of note was the age group of 12 for both appeared to be the case for the boys. However, boys and girls who performed particularly the B12s were faster than the G12s. well. 142 Table 41 continued. MAND cont. BMC cont. Jumping: The boys recorded better jumping Shuttle Run with Object: The times for the boys performance compared to the girls. The 14- were better than the girls. year-olds recorded better jumping performance compared to the 12-year-olds. Quadrant Jump: The number of correct jumps for the girls increased with age and that from Heel-toe: The boys had better and more stable performances than the girls. age 13 the girls outperformed the boys. 143 Table 41 continued. Discriminant Analyses MAND Stepwise Findings Canonical R2 Structure Findings Classification Percentages Misclassified As (n) - First: .41 - Normal: 89% Poor: N = 7; H = 2 High: 66% Normal: P = 19; H = 21 Poor: 27% High: P = 1; N = 15 Framework All Participants: AIS+BMC Shuttle Run With Object - Balance Eyes Open - Basketball Throw - Balance Eyes Closed - Hopping Speed - Dynamic Balance Shuttle Run With Object Second: .09 - Shuttle Run - Hopping Speed - Zigzag Run 144 Table 41 continued. ‘g’ Framework Stepwise Findings Canonical R2 Structure Findings Classification Misclassified As (n) All Participants: - First: .63 No tests strong Normal: 96% Low: N = 5 High: 75% Normal: L = 9; H = 8 Low: 72% High: N = 5 AIS+BMC Dynamic Balance - Second: .15 enough (i.e., < .50). Balance Eyes Open - Quadrant Jump - Hopping-inSquare - Balance Eyes Closed - Hopping Speed - 40m Sprint - Basketball Throw Note. ‘g’ = motoric ‘g’. First = First Discriminant Function, Second = Second Discriminant Function. MAND Framework - P = Poor Motor Coordination Group, N = Normal Motor Coordination Group, H = High Motor Coordination Group, ‘g’ Framework - L = Low Motor Ability Group, N = Normal Motor Ability Group, H = High Motor Ability Group. 145 Initially, it was necessary to identify the underlying constructs of the motor skill instruments used in the current research. Earlier research acknowledges that different factor constructs will emerge from different age groups and different levels of motor difficulty (McCarron, 1982; Rarick, Dobbins & Broadhead, 1976). So, it is imperative to understand what that instrument is assessing, relative to the population under investigation. Factor analysis on motor skill instruments among all participants demonstrated that the three components underlying the MAND were postural control, bi-manual dexterity and muscle power. One component underlying the AIS was labelled explosive power. The three components underlying the BMC were movement coordination, postural control and static balance. On the surface it appears that the MAND, AIS and BMC are competent instruments in assessing motor skills at a basic level. But, when it comes to understanding what it is that these instruments are measuring from a more general perspective, they need to be carefully examined since it appears that what they are assessing could change with the population under investigation. This was borne out in the current research, as the hypothesised factor structures in each case were not upheld in the Malaysian sample. Thus, Burton and Miller’s (1998) recommendation to examine the psychometric properties of an instrument appears warranted. The current research also investigated the concept of GMA through the use of higher-order factor analysis. Past research has reported differences between boys and girls in their performances of fundamental movement skills (Seefeldt & Haubenstricker, 1982; Thomas & French, 1985; Thomas, Michael & Gallagher, 1994). Despite this, Burton and Miller (1982) noted that, some research which examined motor ability, typically ignores the possibility of gender differences at this higher level. Thus, in recognition of these gender differences, the current research tested for the existence of a ‘g’ separately in boys and girls. The results of the first-order factor analysis indicated that movement coordination and postural control were found for both girls and boys, along with some form of balance ability. The type of balance being assessed was static balance for the girls and a more general form of balance for the adolescent boys called kinaesthetic integration. The final motor ability that was only found for the adolescent boys was explosive power. This suggests that, when assessing some form of motor skill, power appears to be more relevant for adolescent boys. These differences in the types of motor ability found for the adolescent boys and girls extends previous research noting gender differences at the motor skill level, by including gender differences at the motor ability level. Therefore, researchers need to be aware that a motor skill instrument may be assessing different motor abilities according to the gender being examined at the time. Despite finding gender differences at motor ability level, the higherorder factor analysis of the girls and boys first-order components both extracted a single 146 motoric ‘g’. The finding of ‘g’ in this manner supports the hierarchical nature of Burton and Rodgerson’s (2001) taxonomy – that a ‘g’ in motor ability can be inferred by performance on either movement skills or movement skill sets. However, the author in this study considers this ‘g’ to be a ‘g’ that is associated with the motor skills assessed by the AIS+BMC. It is highly likely that other ‘g’s could be found from different motor skill instruments. Indeed, by correlating ‘g’s derived from different motor skill instruments could be an avenue for future research to help clarify the existence of GMA. Finally, whilst the results of the higher-order factor analysis that were based on these first-order component structures did not provide definitive evidence for the existence of GMA, neither did it deny the existence of a motoric ‘g’. The motor ability test performances by 330 Malaysian adolescents on motor tasks were then examined, and these varied with age and gender. Participants increased in height, weight and BMI across gender and age. Results also demonstrated no significant interactions between gender and age on fine motor skills of the MAND. However, significant interactions between gender and age were shown on the MANDs gross motor skills of grip strength, and finger-nose-finger, with varied performances reported for the boys and girls across the age groups. For the gross motor skills of jumping and heel-and-toe the boys outperformed the girls. A gender-by-age interaction was also reported for the AIS motor skill of basketball throw with the older boy and girl age groups throwing further; particularly the 14- and 15year-old boys. The boys also outperformed the girls for the AIS motor skills of vertical jump and 40m sprint. Finally, a significant interaction between gender and age was reported for the BMC motor skill of hopping speed. This revealed that although boys outperformed girls at age 12 they deteriorated with an increase in age while the girls improved hopping speed as they became older. The two movement coordination motor skills of the shuttle run and the shuttle-run-with-object revealed that the boys outperformed the girls. Finally, the results for the quadrant jump indicated that the number of correct jumps for the girls increased with age and that from age 13 the girls outperformed the boys. The ability of the combined AIS+BMC motor skills to reliably discriminate and classify Malaysian adolescents into three groups based on their motor performance, was the final focus of the current research. Initially, the MAND (McCarron, 1982) was used to categorise the adolescents into three motor coordination groups. Then, the adolescents were categorised into three motor ability groups by utilising factor scores derived from the motoric ‘g’ found in the higher-order factor analyses. Using stepwise discriminant estimations, specific clusters of motor skills were found to maximally separate the groups derived from these two categorisation methods. However, the motor skills that were consistently reported across 147 both sets of analyses were Balance-Eyes-Open and Balance-Eyes-Closed, Dynamic Balance and Hopping Speed, and Quadrant Jump, Hopping-in-Square, Basketball Throw and ShuttleRun-with-Object. Thus, the motor skills assessing static balance, dynamic balance and postural control appear to help classify the adolescents. This demonstrates that balance has an important role in movement skill proficiency (Burton & Miller, 1998; Proctor & Ruhling, 1981) and that the discriminative power of balance found here also demonstrates that balance ability is an important fundamental motor skill (Rarick et al., 1976). Finally, the overall classification index was reasonable at around 70% when using performance on the MAND to categorise the adolescents, and even better at around 90% using factor scores on the motoric ‘g’ to categorise the adolescents. Despite these positive findings, there were a significant number of misclassifications. These revealed individuals being predicted into a lower group having performed a large number of the motor skills to a lesser standard than their correctly classified cohorts. Conversely, those individuals being predicted into a higher group performed a large number of the motor skills at a standard higher than their correctly classified cohorts. Thus, at a global level, it is possible that certain individuals could be overlooked for further athletic development and this is a concern when developing a rigorous TI program. Therefore, researchers need to be aware and cautious of a single figure of ability and how that figure is used as representative of an individual’s athletic potential. Additionally, it also needs to be acknowledged that the specific classification findings from the discriminant analyses seem to have some utility in identifying Normal performers. The results indicated that the correct classification of the Normal groups was reasonable and, for the High groups, the correct classification was not impressive. Finally, the correct classification for the Poor/Low groups was quite unimpressive. Thus, the motor skills found to reliably discriminate the groups appear to be more relevant to Normal performers, rather than the High performers, which was a focus of the research. 7.2. LIMITATIONS Even though the findings reinforce the importance of effective motor skill instrumentation in TI, there were some limitations inherent in the research that should be acknowledged. A limitation in the current research was the sample size. Although very good initial descriptive data were found for this Malaysian sample, the sample itself was considerably smaller than that examined by the Malaysian Sports Council. This needs to be kept in mind when comparing the findings from this research to past Malaysian research. In addition, it was not possible to validate either the factor analyses or the discriminant analyses findings due to the small sample size. Also, gender could not be examined in great detail and past 148 research has noted gender differences at the motor skill level. Hence, the findings presented here regarding these analyses need to keep this in mind. When examining the concept of GMA, only two of the motor skill instruments were used; namely, the AIS and the BMC. The MAND was ignored. Thus, the motoric ‘g’s found in the higher-order factor analyses was a ‘g’ associated with the AIS and BMC. The inclusion of the MAND and other motor skill instruments in future analyses which test for the existence of GMA, and confirm or deny its existence. There is a need to examine other motor skill instruments which assess not only the same motor abilities found in the current research, but also motor skill instruments assessing other aspects of Burton and Miller’s (1998) foundations of movement skill. The methodology employed to create the motor performance groups for the discriminant analyses used a standardised measurement approach (McCarron, 1982). One problem resulting from this methodology concerns the size of the motor performance groups. Due to the small number of males in one group, discriminant analysis examining possible gender differences could not be done. Therefore, the current study could only provide general information in this regard and gender needs to be considered in future research. The methodology also created relatively large Normal groups which resulted in a high correct classification and hit ratio for Normals. Given that discriminant analysis is quite sensitive to sample size, perhaps future research could use a proportional approach to group sizes in terms of n. Such an approach would create groups better suited to the statistical requirements of discriminant analysis, but would not reflect the real world (Hair et al., 1998; Tabachnick & Fidell, 2007). But, the methodology in the current study was employed because it better reflected what naturally occurs in the general population. 7.3. STRENGTHS Despite these limitations, the present research also had some strong points. The study sought to examine the motor skill performances of Malaysian adolescents in an attempt to find motor skills that could be used in a basic screening instrument/s to identify athletic talent. The analyses found a small set of motor skills that appear to be important for inclusion in a basic screening motor skill instrument for Malaysians. It is clear that motor skills assessing static balance, dynamic balance and postural control should be included in a mass screening test. However, only 13 motor skills assessing explosive power, movement coordination, postural control and static balance were examined. Future investigations need to examine other motor skill instruments assessing different motor abilities to provide a more rounded screening instrument. 149 It was also found that the motor skill performances of the adolescents were sufficiently different from those of other countries to warrant the development of norms specific to Malaysia. These are important for their performances to be compared to standards that are meaningful to Malaysians. Given the marked cultural differences in the importance of physical activity and sport in Malaysia, compared with some Western societies, basing Malaysian performance standards on Western performance standards is inappropriate. However, it should be noted that a considerable amount of effort on the part of Malaysians is needed for them to develop appropriate norms for a wider range of motor skills than those presented here. Finally, the concept of GMA was examined and results of the higher-order factor analyses indicated that a ‘g’ in motor ability exists. The finding of ‘g’ in this manner supports the hierarchical nature of the Burton and Rodgerson’s (2001) taxonomy. That is, a ‘g’ in motor ability can be inferred by performance on either movement skills or movement skill sets. However, the ‘g’ referred to here is associated with the motor skills assessed by the AIS and BMC motor skill instruments. It is possible that other ‘g’s will result from different motor skill instruments. Subsequent examination of these ‘g’s will progress research towards clarifying the existence of GMA. 7.4. CONCLUSIONS On the basis of the findings in this study it can be concluded that: 1. Gender and age influence motor skill performances among Malaysian adolescents. 2. Malaysian adolescent motor skill performances are different from those of other countries, based upon comparisons made to USA norms on the MAND test, and with Australian adolescents on the AIS test percentile scores. 3. The underlying constructs of motor skill instruments used in the current research were identified for this Malaysian sample. 4. Since some of the motor skill instrument constructs were found to be different from their original sources, it is necessary to examine the underlying structures of motor skill instruments if they are being used in populations different from where they were originally sourced. 5. Higher-order factor analyses of the AIS+BMC instrument found a ‘g’ in motor ability for the boys and girls. 6. Discriminant function analysis was useful in highlighting a sub-set of the AIS+BMC motor skills for a mass screening instrument for TI. 150 7.5. RECOMMENDATIONS FOR FURTHER STUDY 1. This was the first time that the MAND instrument was implemented on a Malaysian sample, and valuable normative data were obtained. However, further research utilising other motor skill instruments is needed to establish the reliability, validity, and suitability of these instruments for the Malaysian population. 2. Burton and Miller (1998) have noted 11 foundations of movement skill and two of these- movement coordination and balance- were examined in the current research. The current research found that the motor skill instruments used here only assessed four motor ability components – explosive power, movement coordination, postural control and static balance. However, a broader range of motor skills assessing other foundations of movement skill should be examined in order to develop a more rounded instrument for the mass screening phases of TI. 3. Morphology, perceptual motor skills and psychology are elements that contribute to skilled athletic performance, and all these elements need to be examined when identifying talented athletes. A multidimensional testing instrument consisting of such elements would strengthen the likelihood of identifying talented athletes. 4. The current research tested for a ‘g’ in motor ability. Future research needs to confirm the ‘g’ associated with the combined AIS+BMC motor skill set and extend this examination to include other motor skill instruments. 151 REFERENCES Abbott, A. & Collins, D. (2002). A theoretical and empirical analysis of a 'state of the art' talent identification model. High Ability Studies, 13, 157- 178. Abernethy, B. (1990). Expertise, Visual Search and Information Pick-up in Squash. Perception, 19, 63-77. Abernethy, B. (1991). Visual Search Strategies and Decision Making in Sport. International Journal of Sport Psychology, 22, 189-210. Abernethy, B. (2005). 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Second Factor Analysis Study of Physical Fitness Tests. Research Quarterly, 45(3), 247-256. 1 APPENDIX A Summary of Motor Ability Test Batteries The first reported of motor ability test battery was in 1912. Since then, many researches have been conducted in the area of motor ability instruments from different perspectives of research methodology and data analysis. Around 1930 to 1940, research activities in developing motor ability test batteries were increased based on the strength of the general motor ability concept. However, ever since specificity of motor ability theory had emerged, the investigation on related matter was slowing down. Below is the summary of motor ability test instruments reported according to the year of testing development. Generally, the first half of the reported motor ability batteries was focused more on assessing normal populations. With the growing awareness of the demand of motor assessment across populations, the second half of the reported motor ability batteries was inclusive of assessment of individuals with special needs. 1. Test & Items Sigma Delta Psi Test [Sigma Delta Psi, (1912) in (Clarke and Clarke 1987) pg. 199] 100-yd dash, 120-yd low hurdles, Running high jump, Running broad jump, Shot put, Rope climb, Basketball distance throw, Football distance punt, 100-yd swim, One-mile run, Tumbling, Posture and Scholarship Year 1912 Factor Not reported Claimed/ Measured Age & Sex Not reported Reliability & Not reported Validity Remarks Early test of the general motor ability type (Clarke and Clarke 1987) 2. Test & Items Garfield Motor Ability Test (Garfield 1924) 100 yard dash, picking up paper, leg strength, leg strength, hand 2 strength, tricks, steadiness and tapping. Year 1924 Factor Speed of voluntary movement, accuracy of voluntary movement, Claimed/ control of involuntary movement, strength, and motor adaptability Measured Age & Sex College women Reliability & Not reported Validity Remarks To determine the relationship between motor ability and intelligence quotient (Irvine 1951) 3. Test & Items Brace Motor Ability Test (Brace 1927) A series of twenty individual stunts Year 1927 Factor Agility, Balance, Control, Flexibility, Agility and balance, Claimed/ Strength, Strength and control Measured Age & Sex 8 to 48 years old, male and female Reliability & Reliability range from 0.66 to 0.82 on individual stunts; 0.90 on Validity whole test reported by (National Research Council of the Research Section 1950) Remarks Pioneers study that measure native motor ability. Strongly criticized on its content validity whether the stunts truly measure innate skill (Philips and Wendler 1950). 4. Test & Items Cozens Test of General Athletic Ability (Cozens 1929) Dip, baseball throw for distance, football punt for distance, standing broad jump, bar snap, dodging, and quarter mile run Year 1929 Factor Claimed/ Measured Age & Sex College men Reliability & Reliability 0.97 Validity 0.77 Validity 3 Remarks Inclusive study exploiting the fundamental elements in motor ability (Larson 1941).The test has no proven value as a measure of motor ability (Philips and Wendler 1950). 5. Test & Items Johnson Test of Motor Educability (Johnson 1932) Straddle jump, stagger skip, stagger jump, forward skip, front roll, jumping half turns – right or left, back roll, jumping half turns – right or left alternately, front and back roll alternately, front and back roll combinations and jumping full turns. Year 1932 Factor Native neuro-muscular coordination Claimed/ Measured Age & Sex From 11 years old to adult groups for both sexes Reliability & Reliability 0.97 Validity Validity 0.67 Remarks Probably best test of general motor educability in use at that time (McCloy 1938). Claimed that elements of skill are learned because they are the product of experience and environmental conditions. 6. Test & Items Motor Ability Test for College Women (Alden, Horton et al. 1932) Outdoor test: 50-y dash, jump and reach, bend high hang, baseball throw, through the window ladder, trunk bend Indoor test: 40 yard maze run, trunk bend, ball change, jump and reach Year 1932 Factor Speed, Strength of legs, Abdominal strength, Arm and shoulder Claimed/ coordination Measured Age & Sex College women Reliability & Reliability range from 0.63 to 0.87 Validity And validity range from 0.37 to 0.70 Remarks Authors supposed that the test items were valid to measure general motor ability. 4 7. Test & Items Humiston Test of Motor Ability (Humiston 1937) Alden dodge test;, roll over on mat;, run and climb over box;, run, turn in circle and continue between barriers;, climb ladder;, throw ball, catch it;, and run twenty yards. Year 1937 Factor Running, jumping, equilibrium, getting over obstacles, dodging and Claimed/ hand-eyes coordination Measured Age & Sex College women Reliability & Reliability 0.91 and validity 0.81 Validity 8. Remarks A series of items combined in sequence and run against time Test & Items Kistler Test of Motor Ability (Kistler 1937) Battery 1 Dodge run, burpee test, shot-put Battery 2 General motor capacity, Rogers strength index, shuttle run, standing broad jump Battery 3 Standing board jump, burpee test, shuttle run Year 1937 Factor Age-height-weight-build, strength, skill, health, personality, Claimed/ educability and motor ability Measured Age & Sex Junior and senior high school Reliability & Not reported Validity 9. Remarks Battery 3 considered as the best test suited for all-round use. Test & Items Iowa Revision of the Brace Motor Ability Test (McCloy 1937) Ten stunts in two test batteries of five items. Stunts selected from Brace Motor Ability Tests Year 1937 5 Factor Motor Educability Claimed/ Measured Age & Sex Elementary grades 4-6, junior and senior high school Reliability & Not reported Validity Remarks A combination of previously established tests for the measurement of general motor capacity with separate batteries for each of the sexes. Also classified as Motor Educability 10. Test & Items The Minnesota Ability Test (Graybeal 1937; Bovard and Cozens 1938) Medicine ball throw, a ball catch, standing broad jump, forward rolls and hurdles Year 1937 Factor Claimed/ Measured Age & Sex College women Reliability & Validity 11. Remarks Item of hurdles is more specific to specialised skill (Irvine 1951) Test & Items Metheny Revision of The Johnson Test (Metheny 1938) Front roll, back roll, jumping half turns, jumping full turn. Year 1938 Factor Speed of movement, strength to handle one’s own weight, Motor Claimed/ Educability Measured Age & Sex From 11 years old to adult groups for both sexes Reliability & Reliability 0.97 Validity Validity 0.93 (boys) and 0.87 (girls) Remarks Simplified from The Johnson Test. Four items boys and three items for girls. 6 12. Test & Items Powell and Howe Motor Ability Tests (Powell and Howe 1938; Powell and Howe 1939) a. Three-part of motor ability battery Broad jump, hurdles, scrambles a. Four-part of motor ability battery Broad jump, hurdles, scrambles, velocity throw Year 1938 Factor Power and strength, speed, and coordination Claimed/ Measured Age & Sex High school girls Reliability & Reliability – Three-part of motor ability battery 0.985, Validity Relative validity considered eligible through subjective and objective measures Remarks The four-part motor ability battery was for diagnosis purposes while the three-part motor ability battery was to test general motor ability. 13. Test & Items Scott Test of Motor Ability (Scott 1939; Scott 1943) Battery 1 Basketball throw, Dash, Broad Jump, Wall pass Battery 2 Obstacle Race, Basketball throw, Broad jump Battery 3 Basketball throw, dash, broad jump Year 1939 Factor Strength, motor educability and ability, skill Claimed/ Measured Age & Sex College women Reliability & Reliability ranges from 0.61 to 0.91 on individual test items Validity Validity 0.91 (Battery 1), 0.86 (Battery 2) and 0.90 (battery 3) Remarks The test had been developed using correlation on various combinations situations of tests. On a basis that individuals are different in their innate capacity or potential for acquiring various skill and previous training and experience in motor activities. 7 14. Test & Items Carpenter Test of Motor Educability (Carpenter 1940; Carpenter 1942) Age, height and weight, left and right grips, 6 Brace-type tests, 5 Johnson-type tests, Sargent jump, Burpee test, Standing broad jump, run and under, run and over, run and sit, hop, 30-y dash, ball throw and putting the 4 pound shot Year 1940 Factor Strength, power, agility and motor educability Claimed/ Measured Age & Sex Primary grade level Reliability & Reliability ranges from 0.77 to 0.90 on individual items Validity Validity 0.82 Remarks General motor capacity and general motor ability had been used to extract the individual general motor achievement quotient. 15. Test & Items Larson Test of Motor Ability (Larson 1941) Indoor test: Dodging run, Bar snap, Chinning, Dips, Vertical jump Outdoor test: Baseball throw for distance, Chinning, Bar snap, Vertical jump. Year 1941 Factor Gross body coordination and agility, dynamic strength, motor Claimed/ educability and motor explosiveness Measured Age & Sex College men Reliability & Reliability 0.86 Validity Validity 0.97 (indoor) 0.98 (outdoor) Remarks The first reported test that had been developed using the factor analysis technique. The test did not predict or indicate specific qualities but rather valuable to indicate ability in the basic elements underlying sports skills. 16. Test & Items Barrow Motor Ability Test (Barrow 1954) Battery 1 8 Standing Broad Jump, Softball Throw, Zigzag Run, Wall Pass, Medicine Ball Put, 60-Yard Dash Battery 2 ( Indoor) Standing broad jump, medicine ball put, zigzag run Year 1954 Factor Power, Arm-shoulder coordination, Agility, Hand-eye Claimed/ Coordination, Strength, Speed Measured Age & Sex Junior and senior high school boys and college men Reliability & Reliability range from 0.83-0.93 Validity Remarks 17. Test & Items The Western Motor Ability Test (Campbell and Tucker 1967; Yuhasz 1967), Agility Run, Basketball Throw, Broad Jump, Wall Toss Year 1967 Factor No factors claimed Claimed/ Measured 18. Age & Sex Thirteen years old and above for both sexes. Reliability & Reliability range from 0.89 to 0.95 on individual items (Yuhasz, Validity 1967). Validity not reported Remarks The original source is not available. Test & Items Cratty Six-Category Gross Motor Test (Cratty 1969) Six item test Body perception, gross agility, balance, locomotor agility, ball throwing and ball tracking Year 1969 Factor Claimed/ Measured Age & Sex Reliability & 4 to 24 years old 9 Validity Remarks Two separate six item tests for children with movement problem and perceptual-motor impairment. 19. Test & Items Test of Motor Proficiency (TMP) (Gubbay 1975) Eight fine and gross motor items. Year 1975 Factor Claimed/ Measured Age & Sex 8 to 12 years old Reliability & Validity Remarks 20. Test & Items Bruininks-Oseretsky Test of Motor Performance (BOT) (Bruininks 1978) Gross motor Subtests: Running Speed and Agility, Balance, Bilateral Coordination, Strength Gross and Fine Motor Subtest: Upper-limb Coordination Fine Motor Subtests: Response Speed, Visual-Motor Control, Upper-limb Speed and Dexterity Year Factor Running Speed and Agility Claimed/ Balance, Bilateral Coordination, Strength, Upper-limb Measured Coordination, Response Speed, Visual-Motor Control and Upperlimb Speed and Dexterity. Age & Sex 4.5 to 14.5 years old Reliability & Test-retest reliability range from 0.68 to 0.86 on individual Validity composites for grade six. Content and construct validity have been developed. 10 Remarks Most extensively used in adapted physical education, occupational therapy and physical therapy (Burton and Miller 1998). Factor analysis show that 70% of the total common factor items variance accounted under one factor suggesting a general motor development (Bruininks 1978) and general motor ability (Kraus, Bruininks et al. 1981). However, due to validity issue and others (Hattie and Edwards 1987), the popularity of the test has been questioned (Burton and Miller 1998). 21. Test & Items Basic Motor Ability Tests-Revisied (BMAT-R) (Arnheim and Sinclair 1979) Bead stringing, throwing, marble transfer, flexibility, standing broad jump, rising to stand, and static balance total of eleven items. Year 1979 Factor Eye-hand coordination, finger dexterity, hand speed, flexibility, leg Claimed/ power, agility, static balance, arm strength and eye-foot Measured coordination. Age & Sex 4 to 12 years old Reliability & Validity Remarks 22. Test & Items The Leuven Motor Ability Test (Renson, Beunen et al. 1980) Stick balance, plate tapping, sit and reach, vertical jump, leg lifts, arm pull, bent arm hang, 50m shuttle run, 1 min step test Year 1980 Factor Functional strength, static strength, explosive strength, trunk Claimed/ strength, flexibility, running speed, speed of limb movement, eye- Measured hand coordination, pulse recovery, Age & Sex 13 to 18 years Reliability & Validity Remarks Used only among Belgian adolescence. Even though the test claimed to be a motor ability test, it is more suitable to be categorized as a motor fitness test as strength and endurance are emphasized. 11 23. Test & Items Basic Gross Motor Assessment (BGMA) (Hughes and Riley 1981) Gross motor tasks: Balance, jump, hop, skip, throw, yo-yo and ball handling total of nine tasks. Year 1981 Factor Claimed/ Measured Age & Sex 5.5 to 12.5 years old Reliability & Validity Remarks 24. Test & Items Test of Gross Motor Development (TGMD) (Ulrich 1985; Ulrich 2000) Locomotor: Gallop, hop, horizontal jump, leap, run, skip and slide Object-control: Stationary bounce, catch, kick, two-hand strike, and overarm throw Year 1985 & 2000 Factor Claimed/ Measured Age & Sex 3 to 10 years old Reliability & Validity Remarks 25. Test & Items Movement Assessment Battery for Children Test and checklist (MABC Test) (Henderson & Sugden, 1992) Manual dexterity, ball skills and balance - total of eight tasks Year Factor Claimed/ 1992 12 Measured Age & Sex 4 to 12 years old Reliability & Validity Remarks References Alden, F. D., Horton, M. O., & Caldwell, G. M. (1932). A Motor Ability for University Women for the Classification of Entering Students into Homogenous Group. Research Quarterly, 3, 85120. Arnheim, D. D.& Sinclair, W. A. (1979). The clumsy child. St. Louis, C. V. Mosby. Barrow, H. M. (1954). "Tests of Motor Ability for College Men." Research Quarterly, 25, 253-260. Bovard, J. F., & Cozens, F. W. (1938). Tests and measurements in physical education. Philadelphia, Saunders. Brace, D. K. (1927). Measuring motor ability: A scale of motor ability tests. New York, A. S. Barnes and Company. Bruininks, R. H. (1978). Bruininks-Oseretsky Test of Motor Proficiency. Minnesota, American Guidance Service. Burton, A. W. & Miller, D. E. (1998). Movement skill assessment. Illinios, Human Kinetics. Campbell, W. R., & Tucker, N. M. (1967). An introduction to tests & measurement in physical education. London, G. Bell & Sons Ltd. Carpenter, A. (1940). "Test of Motor Educability for the First Three Grades." Child Development, 11, 293-299. Carpenter, A. (1942). "The Measurement of General Motor Capacity and General Motor Ability in The First three Grades." Research Quarterly, 13, 444-465. Clarke, H. H., & Clarke, D. H. (1987). Application of measurement to physical education. Englewood Cliffs, New Jersey, Prentice-Hall. Cozens, F. W. (1929). The measurement of general athletic ability in college men. Eugene, University of Oregon Press. Cratty, B. J. (1969). Perceptual motor behavior and educational processes. Springfield, IL, Charles C. Thomas. Garfield, E. J. (1924). "Measurements of Motor Ability." Archives of Psychology, 9, 62. Graybeal, E. (1937). Measurement of outcomes in physical education. Minnesota, University Minnesota Press. 13 Gubbay, S. S. (1975). The clumsy child: A study of developmental apraxic and agnosic ataxia. London, Saunders. Hattie, J., & Edwards, H. (1987). "A Review of the Bruininks-Oseretsky Test of Motor Proficiency." British Journal of Educational Psychology, 57, 104-113. Henderson, S. E.,& Sugden, D. A. (1992). Movement assessment battery for children. Sidcup, Kent, England, Therapy Skill Builders. Hughes, J. E., & Riley, A. (1981). "Basic Gross Motor Assessment: Tool for use with Children Having Minor Motor Dysfunction." Physical Therapy, 61, 503-511. Humiston, D. A. (1937). "A Measurement of Motor Ability in College Women." Research Quarterly, 8, 181-185. Irvine, C. M. (1951). The critical evaluation of general motor ability tests in physical education. Human Movement and Exercise Science. Perth, University of Western Australia. Johnson, G. B. (1932). "Physical Skill Tests for Sectioning Classes into Homogenous Units." The Research Quarterly, 3, 128-136. Kistler, J. W. (1937). "The Establishment of Bases for Classification of Junior and Senior High School Boys into Homogenous Groups for Physical Education." Research Quarterly, 8, 1118. Kraus, H., Bruininks, R. H., et al. (1981). "Structure of Motor Abilities in Children." Perceptual and Motor Skills, 52, 119-129. Larson, L. A. (1941). "A Factor Analysis of Motor Ability Variables and Tests, with Tests for College Men." Research Quarterly, 12, 499-517. McCloy, C. H. (1937). "An analytical Study of the Stunt Type Test as a Measure of Motor Educability." Research Quarterly, 8, 46-55. McCloy, C. H. (1938). Tests and measurement in health and physical education. New York, F. S. Crofts and Company. Metheny, E. (1938). "Studies in the Johnson Test as a Test of Motor Educability." Research Quarterly, 9, 105-114. National Research Council of the Research Section (1950). Measurement and evaluation materials in health, physical education, and recreation. Washington, D. C., American Association for Health, Physical Education, and Recreation. A Department of the National Education Association. Philips, M. and A. J. Wendler (1950). General Motor Skills. Measurement and evaluation materials in health, physical education, and recreation. N. R. C. O. T. R. Section. Washington, D.C., American Association for Health, Physical Education, and Recreation. A Department of the National Education Association. Powell, E. and E. C. Howe (1938). "Wellesley College Studies in Hygiene and Physical Education Test and Analysis of General Motor Ability." Research Quarterly - Supplement, 9, 49-66. 14 Powell, E. and E. C. Howe (1939). "Motor Ability Tests for High School Girls." Research Quarterly, 10, 81-88. Renson, R., G. Beunen, et al. (1980). Description of Motor Ability Tests and Anthropometric Measurements. In Somatic and Motor Development of Belgian Secondary Schoolboys. Norm and Standards. M. Ostyn, J. Simons, G. Beunen, R. Renson and D. Van Gerven, (eds). Leuven, Leuven University Press. Scott, M. G. (1939). "The Assessments of Motor Abilities of College Women through Objective Tests." Research Quarterly, 10, 63-83. Scott, M. G. (1943). "Motor Ability Tests for College Women." Research Quarterly, 14, 402-405. Ulrich, D. A. (1985). Test of gross motor development. Austin Tex, PRO-ED. Ulrich, D. A. (2000). Test of gross motor development: Examiner's manual. Austin Tex, Pro-Ed. Yuhasz, M. S. (1967). The Western Motor Ability Test, Physical Fitness Research Laboratory, The University of Western Ontario. In An introduction to tests & measurement in physical education. W. R. Campbell and N. M. Tucker (eds.). London, G. Bell & Sons Ltd. 15 APPENDIX B LIST OF TABLES Table 1. Table 2. Table 3. Table 4. Table 5. Guilford’s Two Dimensional System (Guilford, 1958) ................................................................... 15 Fleishman’s Structure of Motor Ability (Fleishman,1964) ............................................................. 15 Harrow Taxonomy of the Psychomotor Domain (Harrow, 1972) .................................................. 16 Basic Abilities of Motor Performance Domain (Baumgartner & Jackson, 1975) .......................... 17 Gentile’s Taxonomy of Movement Tasks (Gentile, 1987) ............................................................... 17 LIST OF FIGURES Figure 1. Figure 2. Figure 3. Classification System for General Motor Ability, Motor Fitness &Physical Fitness (Clarke, 1967). Movement Skill Taxonomy (Burton & Miller, 1998) ......................................................................... Four Levels of Movement Skill Taxonomy & General Motor Ability (Burton & Rodgerson, 2001) LIST OF HUMAN MOVEMENT TAXONOMY Table 1. Guilford’s Two Dimensional System (Guilford, 1958) Part of body Type of Ability Strength Impulsion Speed involved Gross Static Dynamic Precision Precision Coordination General General Static Dynamic Gross bodily strength reaction balance balance coordination Flexibility time Trunk Trunk Trunk flexibility strength Limbs Limb Limb-trust strength Hand Arm Arm speed steadiness Tapping Arm aiming Hand Leg flexibility Hand dexterity aiming Finger Finger Finger dexterity speed Table 2. Fleishman’s Structure of Motor Ability Physical Proficiency Psychomotor Abilities 1. Extent flexibility 1. Control precision 2. Dynamic flexibility 2. Multi-limb coordination 3. Explosive strength 3. Response orientation 4. Static strength 4. Reaction time 5. Dynamic strength 5. Speed of arm movement 6. Trunk strength 6. Rate control 7. Gross body coordination 7. Manual dexterity 8. Gross body equilibrium 8. Finger dexterity 9. Cardiovascular endurance 9. Arm-hand steadiness 10. Wrist-finger speed 11. Aiming 16 Physical Fitness Motor Fitness General Motor Ability Arm-eye Muscular coordination power Agility Muscular Muscular Circulo- strength endurance endurance Flexibility Speed Foot-eye coordination Organic soundness and proper nutrition Figure 1. Classification System for General Motor Ability, Motor Fitness and Physical Fitness (Clarke, 1967). Table 3. Harrow Taxonomy of the Psychomotor Domain (Harrow, 1972) 1.00 Reflex movements 1.10 Segmental reflexes 1.20 Intersegmental reflexes 1.30 suprasegmental reflexes 2.00 Basic-fundamental movements 2.10 Locomotor movements 2.20 Non-locomotor movements 2.30 Manipulative movements 3.00 Perceptual abilities 3.10 Kinaesthetic discrimination 3.20 Visual discrimination 3.30 Auditory discrimination 3.40 Tactile discrimination 3.50 Coordinated abilities 4.00 Physical Abilities 4.10 Endurance 4.20 Strength 4.30 Flexibility 4.40 Agility 5.00 Skilled movements 5.10 Simple adaptive skill 5.20 Compound adaptive skill 5.30 Complex adaptive skill 6.00 Non-discursive communication 17 6.10 Expressive movement 6.20 Interpretive movement Table 4. Basic Abilities of Motor Performance Domain (Baumgartner & Jackson, 1975) A Muscular strength 1. Arm strength 2. Leg strength B Muscular power 1. Arm power 2. Leg power C Muscular endurance 1. Arms and shoulder girdle 2. Abdominal muscles 3. Cardiorespiration D Basic movement pattern 1. Running speed 2. Running agility 3. Jumping 4. Throwing ability Table 5. Gentile’s Taxonomy of Movement Tasks (Gentile, 1987) Performer Stable Environment Stationary Inter-trial Transport No Object No Object manipulation manipulation manipulation manipulation 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 variability No variability Moving Inter-trial variability No variability 18 Functional movement skills Specialized movement skills Fundamental movement skills Early movement milestone Motor abilities Foundations of movement skills Figure 2. Movement Skill Taxonomy (Burton & Miller, 1998) Movement Skills Movement Skill Sets Movement Skill Foundations General Motor Ability Figure 3. Four Levels of Movement Skill Taxonomy & General Motor Ability (Burton & Rodgerson, 2001) References Baumgartner, T. A. & Jackson, A. S. (1975). Measurement for Evaluation in Physical Education. Hopewell, New Jersey: Houghton Mifflin Company. Burton, A. W. & Miller, D. E. (1998). Movement Skill Assessment. Illinios: Human Kinetics. Burton, A. W. & Rodgerson, R. W. (2001). New Perspectives on the Assessment of Movement Skills and Motor Abilities. Adapted Physical Activity Quarterly, 18, 347-365. Clarke, H. H. (1967). Application of Measurement to Health and Physical Education. Englewood Cliffs, New Jersey: Prentice-Hall, Inc. Fleishman, E. A. (1964). The Structure and Measurement of Physical Fitness. New Jersey: Prentice-Hall. 19 Gentile, A. M. (1987). Skill Acquisition: Action, Movement, and Neuromotor Processes. In J. H. Carr, R. B. Shepherd, A. M. Gordon, A. M. Gentile & J. M. Held (Eds.), Movement Science: Foundations for Physical Therapy in Rehabilitation. Rockville, MD: Aspen Publishers. Guilford, J. P. (1958). A System of Psychomotor Abilities. American Journal of Psychology, 71, 164-174. Harrow, A. J. (1972). A Taxonomy of the Psychomotor Domain a Guide for Developing Behavioral Objectives. New York: David McKay Company, INC. APPENDIX C The selection of the motor skills for the balance and movement coordination test is based on information below: 1. Malaysian Sports Council (Majlis Sukan Negara, Malaysia) conducted a talent identification and development program in conjunction with hosting the Commonwealth Games 1998. A talent identification and fitness testing handbook was published by Institut Sukan Negara in 1998 (Institute of Sport) containing the testing procedures, the normative data of 11 – 14 years adolescents and normative data of Malaysian National athletes. Testing conducted and normative data obtained among Malaysian school children are: 1. Body measurements – height, arm span, sitting height, body mass 2. Strength & power – vertical jump, weight throw 3. speed – 40m sprint 4. Agility – agility hexagon 5. endurance – 800m run Listed testing as indicate above shown that the component of balance ability is not included. In addition, task analysis on the listed testing also employed that there are less element of propulsion, running action and ability to change directions, while moving and executing the manoeuvres continuously that specify movement coordination. On the other hand, two balance items (blind stork and rotating stork) were conducted among Malaysian athletes (as listed in the table below). However, the normative data obtained at the 50 percentile score on the conducted balance test (blind stork and rotating stork) were varies (Blind Stork: Female, minimum = 17.8s, maximum = 94.09s; Male, minimum = 11.97s, maximum = 106.19s and Rotating Stork: Female, minimum = 24.37s, maximum = 360.49s; Male, minimum = 50.97s, maximum = 342.99s). 20 Malaysian athletes 50 percentile score Female Blind stork (s) Male Rotating stork Blind stork (s) Rotating stork (s) (s) artistic gymnastics, 94.09 24.37 97.10 65.12 rhythmic gymnastics 29.11 212.08 - - badminton, 17.8 203.4 19.6 81.0 bowling, 72.2 81.4 35.03 59.63 boxing, - - - - cricket, - - - - cycling, 17.52 76.73 37.95 50.97 diving, 44.05 43.61 106.19 257.00 hockey, 36.97 71.14 64.46 171.69 lawn bowling, 37.38 48.70 23.09 71.10 middle distance runners 23.00 36.50 23.46 79.85 netball, 42.12 38.70 - - sepaktakraw, - - - - racewalking, 18.03 84.46 11.97 153.75 - - - - 45.25 45.61 31.70 37.97 - - - - 61.84 360.49 47.20 342.99 36.3 30.3 rugby, shooting, silat olahraga, squash weight lifting - Therefore, investigation focusing on the balance and motor coordination is conducted in this research due to: 1. the range of scores on balance tests were varies among athletes and 2. minimal aspect of body propulsion and rapid change directions while moving and executing the tasks continuously on the selected test items 2. There is very limited data pertaining to children’s health and physical fitness in Malaysia and only limited findings have been reported or published (Singh, Singh & Larmie, 2004). Research and published data by Singh, Singh and Larmie (2004) focused on health-related fitness components tests and none on skill-related components test (the balance and motor coordination test). 21 Reference: Singh, R., Singh, M., Larmie, E. T. (2004). An Exercise Intervention Package on Health-Related Physical Fitness in Malaysian Secondary School Boys. In Chin, M., Hensley, L. D., Cote, P., Chen, S. (2004). Global Perspectives in the Integration of Physical Activity, Sport, Dance and Exercise Science in Physical Education: From Theory to Practice, In 2nd International Conference for Physical Educators (ICPE 2004). The Hong Kong Institute of Education. 3. Research and published data by Jawis, Singh, Singh & Yassin (2005) on sepak takraw players on 3age categories (15, 18 & 23 years old) also focused on health-related fitness. Reference: Jawis, M. N., Singh, R., Singh, H. J., Yassin, M. N. (2005). Anthropometric and Physiological Profiles of Sepak Takraw Players. British Journal Sports Medicine, 39: 825-829 The variations of score ranges on balance tests as well as minimal aspect of body propulsion and rapid direction changes directed this research to focus on the balance and movement coordination components. In addition, this research provided an opportunity to widen research and publish data on the skill-related components among Malaysian adolescents. APPENDIX D PENERANGAN RINGKAS PROSEDUR PENTADBIRAN UJIAN DAN BORANG SKOR Ujian McCarron Assessment of Neuromuscular Development (MAND Test) Bahagian ini memberi penerangan ringkas berkenaan dengan prosedur pentadbiran ujian McCarron Assessment of Neuromuscular Development (MAND). Penerangan protocol ujian yang lebih komprenhesif boleh diperolehi di dalam manual ujian. McCarron Assessment of Neuromuscular Development (MAND) mengandungi sepuluh jenis tugasan motor. Lima tugasan dikategorikan sebagai Tugasan Motor Halus dan lima lagi dikategorikan sebagai Tugasan Motor Kasar. Berikut adalah senarai tugasan: Tugasan Motor Halus Tugasan Motor Kasar Manik dalam kotak Kekuatan gengaman tangan Manik dalam batang rod Pergerakan jari-hidung-jari Ketukan jari Lompatan Nat dan skru Jalan tumit-hujung jari Rod gelungsor Imbangan satu kaki 22 TUGASAN MOTOR HALUS 1. Manik dalam kotak Tugasan ini memerlukan peserta untuk mengubah manik satu persatu dari kotak yang penuh dengan manik ke dalam kotak yang kosong (kotak standard) dengan menggunakan satu tangan sepantas yang mungkin dalam 30 saat. Penguji menunjukcara tugasan dan memberikan arahan kepada peserta. Ulangi prosedur yang sama untuk tangan yang lain. Peserta dibenarkan membuat latihan awal jika perlu. Arahan: 1. “Dengan mengunakan tangan kanan, ambil manik dalam kotak satu persatu dan pindahkan di dalam kotak kosong yang disediakan. Lakukan tugasan sepantas yang boleh sehingga arahan berhenti. Ingat, hanya satu manik dalam satu masa. Sekiranya manik yang anda ambil jatuh, biarkan dan teruskan aktiviti memindahkan manik ke dalam kotak yang disediakan.” 2. “Dengan mengunakan tangan kiri, ambil manik dalam kotak satu persatu dan pindahkan di dalam kotak kosong yang disediakan. Lakukan tugasan sepantas yang boleh sehingga arahan berhenti. Ingat, hanya satu manik dalam satu masa. Sekiranya manik yang anda ambil jatuh, biarkan dan teruskan aktiviti memindahkan manik ke dalam kotak yang disediakan.” Rekod hanya jumlah manik yang diletakkan ke dalam kotak yang kosong dalam masa yang diberikan. Skor untuk tugasan ini adalah jumlah manik yang berjaya diubah oleh kedua-dua tangan dengan betul. 2. Manik dalam batang rod Di dalam tugasan ini, peserta dikehendaki untuk memasukkan manik kayu berbentuk silinder ke dalam rod. Tangan tidak dominan memegang bahagian bawah rod dengan teguh manakala tangan dominan akan memasukkan manik ke dalam rod satu persatu sepantas mungkin dalam 30 saat. Keduadua tangan tidak diletakkan di atas meja dan bebas bergerak untuk mengubah manik. Ulangi prosedur yang sama dengan mata ditutup. Peserta dibenarkan melakukan latihan awal sekiranya perlu. Arahan: “Ambil manik satu persatu dan masukkan ke dalam batang rod seperti ini. Lakukan sepantas yang boleh sehingga saya beritahu untuk berhenti. Pastikan untuk memegang batang rod, lengan anda jauh sedikit dari badan.” 23 Rekodkan jumlah manik yang berjaya dimasukkan ke dalam rod dalam masa yang diberikan. Skor untuk tugasan ini adalah jumlah semua manik yang berjaya dipindahkan dengan betul dengan mata terbuka dan mata tertutup. 3. Ketukan Jari Peserta dikehendaki untuk menepuk jari telunjuknya keatas dan ke bawah dalam masa 10 saat. Jari telunjuk hendaklah menyentuh gelang getah apabila digerakkan ke atas dan menyentuh lantai papan apabila digerakkan ke bawah. Ketinggiang gelang getah hendaklah berada pada paras yang sama dengan kedudukan jari telunjuk ketika jari selari dengan platform. Ulangi prosedur ini dengan tangan yang sebelah lagi. Peserta dibenarkan melakukan latihan awal jika perlu. Arahan: “Gengam tangan anda, tetapi biarkan ibu jari dan jari telunjuk terkeluar. Sekarang gerakkan jari telunjuk anda ke atas dan ke bawah supaya menyentuh papan dan getah pengikat. Lakukan gerakan ketukan jari sepantas yang boleh. Gerakkan hanya jari telunjuk.” Perhati dan rekodkan pelakuan motor ini (rentak sentuhan, gerakan tangan dan jari yang lain, lebihan gerakan di lengan dan setuhan jari yang tidak lengkap). Skor tugasan ini adalah jumlah keseluruhan sentuhan yang lengkap dan pemarkahan perlakuan motor yang diperhatikan untuk kedua-dua tangan. 4. Nat dan skru Di dalam tugasan ini, peserta dikehendaki untuk memusing set besar skru ke dalam nat sepantas yang boleh. Tangan dominan yang memegang skru akan memusing manakala tangan tidak dominan memegang nat yang tidak bergerak. Kedua-dua tangan berada di hadapan peserta tanpa diletakkan di meja atau di pangkuan. Ulangi prosedur yang sama untuk set skru yang kecil. Arahan: “Pegang nat dengan tangan ini (tangan non-dominan) dan pusingkan skru (tangan dominan) ke dalam nat. Pusingkan skru sepantas yang boleh hingga ke hujung.” Skor tugasan individu dikira dengan menolak tempoh masa yang di ambil untuk memusingkan skru ke hujung nat dari skor 100. Rekodkan skor dengan mencampurkan kedua-dua skor untuk set skru kecil dan besar. 5. Rod gelunsor 24 Tugasan ini mengkehendaki peserta mengerakkan penyepit gelungsor seperlahan yang boleh di dalam rod gelungsor dengan menggunakan otot lengan dan tangan. Peserta berdiri ketika melakukan tugasan dengan rod gelungsor berada di paras pinggang dan ±30 sm dari badan. Kedua-dua tangan perlu melakukan tugasan ini. Tangan kiri akan melakukan pergerakan dari arah kiri ke kanan manakala tangan kanan akan melakukan pergerakan dari arah kanan ke kiri. Arahan: “Selama ini, anda telah disuruh untuk melakukan tugasan motor sepantas yang boleh. Kali ini, kita akan melakukan sesuatu yang berlainan. Saya mahu anda melakukan aktiviti ini seperlahan yang boleh. Ingat, lebih perlahan lebih baik. Gerakkan penyepit gelungsur seperlahan yang boleh, seperti ini.” Rekod masa yang digunakan untuk memggerakkan penyepit di rod gelunsor di antara dua penghujung rod. Peserta mungkin akan mengambil masa yang lama untuk menyempurnakan tugasan kerana semakin lambat pergerakan semakin baik skor. Walaubagaimana pun skor maksimum 30 saat diberikan kepada setiap tangan. Rekodkan pemarkahan tingkahlaku pergerakan ke atas kadar pergerakan, ganguan, perubahan kepala-badan, dan pergerakan badan berlebihan juga dikira. Jumlahkan skor kedua-dua tangan untuk memperolehi jumlah skor keseluruhan tugasan. TUGASAN MOTOR KASAR 1. Kekuatan tangan Tugasan ini mengkehendaki peserta memegang alat dynamometer dengan lengan tegak ke hadapan pada paras bahu dan mengengam pemegang alat dynamometer sekuat yang boleh. Setiap tangan perlu melakukan dua percubaan dan bergilir tangan antara percubaan. Skor terbaik di antara dua percubaan direkodkan dalam kilogram. Arahan: “Gengam pemegang alat ini sekuat yang boleh” 2. Pergerakan jari-hidung-jari Di dalam tugasan ini, peserta dikehendaki menyentuh hujung extensi jari tangan sebelah lagi dengan jari telunjuk dan bergerak untuk menyentuh hujung hidung dalam tempoh 10 saat atau lebih kurang lima kali ulangan sentuhan. Peserta mengulangi prosedur yang sama untuk kedua-dua belah tangan dengan mata terbuka dan mata tertutup menjadikan jumlah tugasan ini mengandungi empat percubaan. 25 Arahan: “ Ini bukanlah ujian kepantasan; Cuma relaks dan lakukan yang terbaik. Letakkan tangan kiri anda tegak ke hadapan dan tunjukkan jari anda ke dinding. Sekarang, tunjukkan hanya jari anda ke dinding sebelah kanan. (Jari telunjuk tangan kiri mengarah ke kanan dan menunjuk ke sebelah kanan dinding). Dengan jari telunjuk kanan anda, sentuh hujung hidung anda dan hujung jari anda seperti ini.” Skor tingkahlaku pergerakan lengan, jari telunjuk pada tangan yang diextensikan, titik sentuhan, bengkokan siku dan sentuhan adalah direkodkan. Jumlah keseluruhan skor adalah jumlah skor pemarkahan sentuhan jari-hidung-jari dilakukan ketika mata terbuka dicampurkan dengan skor ketika mata tertutup untuk kedua-dua belah tangan kiri dan kanan. 3. Lompatan Peserta dikehendaki melompat sejauh yang boleh dengan kedua-dua kaki berada di belakang garisan. Kualiti tingkah laku pergerakan iaitu henjutan kaki, pengunaan tangan dan lengan, imbangan badan dan mendarat adalah dinilai. Jumlah keseluruhan skor adalah dengan mencampurkan jarak lompatan dengan skor tingkah laku pergerakan yang diperhatikan. Arahan: “Dengan kedua-dua belah kaki, lompat ke hadapan sejauh yang boleh.” 4. Jalan tumit-hujung jari Di dalam tugasan ini, peserta dikehendaki untuk berjalan ke hadapan di atas garisan tegak sepanjang 10 kaki dengan meletakkan tumit (kaki hadapan) di hadapan jari kaki (kaki belakang) berterusan dan sebaliknya apabila bergerak mengarah ke belakang. Peserta boleh memakai kasut bertapak rata, atau berkaki ayam, atau berstokin untuk melaksanakan tugasan dengan tangan diletakkan di pinggang. Arahan: 1. Ke hadapan “Relaks dan lakukan tugasan ini sebaik yang boleh. Letakkan kedua-dua tangan anda di pinggang dan jalan di atas garisan dengan meletakkan tumit anda di hadapan jari kaki, menyentuh tumit dengan jari kaki di setiap langkah. Mulakan dari sini (hujung tali pita) dan jalan sehingga ke sebelah hujung sana.” 2. Ke belakang “Kali ini, jalan mengundur ke belakang. Letakkan kedua-dua tangan anda di pinggang dan jalan di atas garisan dengan meletakkan jari kaki anda di belakang tumit, jari kaki dengan tumit bersentuhan di setiap langkah.” 26 Tingkah laku pergerakan diperhatikan ke atas bahagian lengan, kaki, jarak tumit dan jari kaki, gerakan dan posisi kaki diberi pemarkahan dan direkodkan. Jumlah keseluruhan skor adalah skor pergerakan berjalan ke hadapan dicampur dengan skor pergerakan ke belakang. 5. Imbangan satu kaki Peserta dikehendaki mengekalkan imbangan badan ketika berdiri di atas satu kaki selama maksima masa 30 saat. Peserta dibenarkan untuk mengerakkan lengan dan tangan untuk mengekalkan imbangan. Percubaan dilaksanakan untuk kedua-dua belah kaki kiri dan kanan ketika mata terbuka dan tertutup. Mulakan catatan masa apabila satu kaki di angkat dari lantai dan hentikan masa apabila peserta mula untuk melompat, atau mengangkat kaki atau tangan menyentuh lantai. Percubaan kedua akan diberikan kepada peserta sekiranya peserta gagal untuk mengekalkan imbangan untuk sekurangkurangnya 10 saat. Arahan: 1. Mata terbuka “Berdiri di atas satu kaki selama yang boleh sehingga saya beritahu anda untuk berhenti”. 2. Mata tertutup “Kali ini, berdiri di atas satu kaki dengan mata tertutup. Ingat, anda mesti pejamkan mata anda”. Rekodkan masa imbangan dalam saat. Jumlah keseluruhan skor adalah skor masa imbangan kaki kiri dan kaki kanan ketika mata dibuka dicampurkan dengan masa imbangan kaki kiri dan kaki kanan ketika mata ditutup. 27 McCarron (MAND) Assessment of Neuromuscular Development Kad Skor NDI __________ NAMA : ________________________________________ TARIKH : _____________ TARIKH LAHIR : ____________________ UMUR KETIKA UJIAN : _____________ JANTINA :Lelaki /Perempuan TANGAN DOMINAN: Kanan /Kiri KAKI DOMINAN: Kanan /Kiri TINGGI : __________BERAT : ______DIAGNOSIS: ___________________________ MANIK DALAM Kanan ____ Kiri ____ KOTAK Jumlah Skala skor ____ _____ (jumlah manik dalam 30 saat) MANIK DALAM Mata Terbuka Mata Tertutup Jumlah Skala skor ROD ____ ____ ____ _____ Kanan ____ Kiri ____ Jumlah Skala skor ____ _____ (gunakan manik berbentuk silinder sahaja – jumlah manik dalam 30 saat) KETUKAN JARI (gunakan lampiran skor) NAT DAN SKRU Besar Kecil Jumlah Skala skor (masa dalam saat 100 - ___ = ____ 100 - ___ = ____ ____ _____ untuk menyempurnakan tugasan) ROD GELUNGSUR Skala skor (gunakan lampiran _____ skor) Sub-Jumlah _____ PURATA MOTOR HALUS _____ 28 KEKUATAN Kanan ____ Kiri ____ GENGAMAN (terbaik Jumlah Skala skor ___ _____ dari dua percubaan untuk setiap tangan) JARI-HIDUNG-JARI (gunakan lampiran skor) Mata Terbuka Mata Tertutup Jumlah Skala skor ____ ____ ___ _____ LOMPATAN Jumlah Skala skor (gunakan lampiran ___ _____ skor) JALAN TUMIT- Ke hadapan Ke belakang Jumlah Skala skor HUJUNG JARI _____ _____ ___ _____ (gunakan lampiran skor) IMBANGAN SATU KAKI (masa dalam saat sehingga 30 saat) Mata terbuka Kanan ____ Kiri ____ Jumlah ___ Mata tertutup Kanan ____ Kiri ____ Jumlah ___ Jumlah Skala skor ___ _____ Sub-Jumlah _____ PURATA MOTOR KASAR _____ KESELURUHAN PURATA MOTOR _____ 29 KAD SKOR MAND NAMA : ________________________________ LAMPIRAN PROTOKOL KETUKAN JARI KANAN KIRI A. Rithma ________ ________ B. Pergerakan tangan tak berkenaaan ________ ________ C. Pergerakan tangan yang berlebihan ________ ________ D. Kesempurnaan jarak pergerakan ________ ________ E. Jumlah ketukan ________ ________ ________ ________ KANAN KIRI A. Pertukaran kadar kelajuan _______ ________ B. Gangguan _______ ________ C. Perpindahan pergerakan kepala-badan _______ ________ D. Pergerakan badan tak berkenaan _______ ________ E. Masa diambil _______ ________ _______ ________ JUMLAH ROD GELUNGSUR JUMLAH JARI-HIDUNG-JARI MATA TERBUKA MATA TERTUTUP KANAN KIRI KANAN KIRI A. Kelicinan pergerakan tangan _______ _______ _______ ________ B. Ketetapan jari telunjuk _______ _______ _______ ________ C. Titik sentuhan _______ _______ _______ ________ D. Bengkokan siku _______ _______ _______ ________ E. Sentuhan/penekanan _______ _______ _______ ________ JUMLAH _______ JUMLAH ________ 30 LOMPATAN LOMPAT 1 LOMPAT 2 LOMPAT 3 A. Henjutan _____ _____ _____ B. Kegunaan tangan _____ _____ _____ C. Imbangan badan _____ _____ _____ D. Mendarat dengan lutut dibengkokan _____ _____ _____ E. Jarak mendarat _____ _____ _____ JUMLAH _____ _____ _____ JALAN TUMIT-JARI KAKI KE HADAPAN KE BELAKANG A. Posisi tangan _______ ________ B. Kaki di atas tali pita _______ ________ C. Jarak tumit-jari kaki _______ ________ D. Kelicinan pergerakan _______ ________ E. Keselarian kedudukan kaki _______ ________ _______ ________ JUMLAH 31 PROTOKOL PEMARKAHAN UJIAN JARI-HIDUNG-JARI (Pemerhatian masa 10 saat untuk setiap percubaan) MATA MATA TERBUKA TERTUTUP Kanan A Pergerakan tangan 4. Arah gerakan tangan adalah licin 2. Pergerakan tangan sedikit tidak sekata atau bergetar 1. Gerakan tangan mengelirukan dan terhenjuthenjut B Jari telunjuk pada tangan yang didepakan kehadapan 4. Kekal tetap 2. Sedikit bergoyang dan bergetar 1. Jelas bergoyang dan bergetar C Titik sentuhan 4. Titik sentuhan di hujung hidung dan di hujung jari telunjuk yang didepakan 2. Terlepas salah satu titik sentuhan di hujung hidung dan di hujung jari telunjuk yang didepakan 1. Terlepas di kedua-dua titik sentuhan di hujung hidung dan di hujung jari telunjuk yang didepakan D Bengkokan siku (pergerakan kedalam) 4. Lengan kekal didepakan 2. Siku sedikit bengkok (kurang dari 30º) 1. Bengkok siku yang jelas (lebih daripada 30º) Kiri Kanan Kiri 32 E Tekanan sentuhan 4. Menyentuh dengan lembut pada hujung jari yang didepakan kehadapan dan hujung hidung 2. Kelihatan menekan jari telunjuk pada tangan yang didepakan ke hadapan atau menekan hujung hidung sekali atau dua kali 1. Kelihatan menekan jari telunjuk pada tangan yang didepakan ke hadapan atau menekan hujung hidung tiga kali atau lebih Jumlah 33 PROTOKOL PEMARKAHAN UJIAN LOMPATAN (Pergerakan badan berdasarkan kepada keseluruhan pergerakan yang diperhatikan ketika ketiga-tiga lompatan dilakukan) A Lompatan 4. Lompatan seimbang keudara dari kedu-duaa belah kaki 2. Lompatan yang janggal ke udara, lebih menggunakan sebelah kaki untuk melompat. 1. B Lompatan jangga, keupayaan melompat keudara terhad. Penggunaan tangan 4. Tangan membantu dengan sedikit pergerakan ke hadapan dan kembali ke sisi 2. Sedikit bantuan tangan yang bergerak dengan lemah 1. Tangan dikeraskan; tidak membantu gerakan C Imbangan badan 4. Mendarat stabil, pusat graviti di tengah (tetap di kedudukan mendarat) 2. Mendarat tidak stabil tetapi berupaya menmperolehi imbangan 1. Mendarat tidak stabil; mengambil langkah ke hadapan atau ke belakang atau menggunakan tangan untuk mengelak dari jatuh. D Mendarat dengan lutut dibengkokkan 4. Mendarat dengan licin dengan kedua-dua belah kaki serentak dengan sedikit bengkok pada lutut untuk menyerap hentakan E 2. Sedikit mendarat dengan kaku, bengkokan lutut yang terhad 1. Mendarat dengan lutut yang kaku; badan bergegar ketika mendarat Jarak lompatan Jarak direkodkan yang terjauh dari tiga percubaan Jumlah 34 PROTOKOL PEMARKAHAN UJIAN JALAN TUMIT-HUJUNG JARI (Individu berjalan pada jarak 10 kaki) A B Pergerakan tangan/badan 4. Kedua-dua tangan kekal di pinggul 2. Mengerakkan satu tanggan dari pinggul 1. Mengerakkan kedua-dua tanggan dari pinggul Kaki 4. Mengekalkan kedua-dua kaki di atas pita garisan 2. Kaki diubahsuai dari garisan sekali atu dua kali (Bila kurang dari separuh dari pita dpijak, kaki dikira sebagai tidak memijak di atas pita garisan) 1. C Kaki diubahsuai dari garisan melebihi dari tiga kali Jarak tumit dan hujung jari 4. Kaki diletakkan lebih kurang satu inci dari hujung jari 2. Kaki diletakkan lebih dari satu inci dari hujung jari sekali sekala 1. Kaki diletakkan lebih dari satu inci dari hujung jari tiga kali atau lebih D Pergerakan 4. Berjalan licin ke hadapan 2. Sedikit berhenti ketika pergerakan kehadapan 1. Perubahan berat ke hadapan dan ke belakang ketika berjalan E Keselarian tapak 4. Kedua-dua kaki selari dengan pita 2. Langkah yang betul, tetapi kemudian berputar pada arah (20º atau lebih) dari garisan 1. Langkah yang berputar pada arah (20º atau lebih) dari garisan Ke Ke Hadapan Belakang 35 Keselarian tapak Putaran Jumlah 20º PROTOKOL PEMARKAHAN UJIAN KETUKAN JARI (Pemerhatian untuk tempoh masa 10 saat untuk setiap tangan) KANAN A Ritma ketukan 4. Sekata, ritma ketukan yang konsisten 2. Gangguan ketukan sekali sekala, tetapi berupaya kembali konsisten 1. B C Berubah-ubah, ketukan tidak beritma Pergerakan tangan tidak berkenaan 4. Bergerak hanya jari telunjuk, gengaman tangan kekal 2. Ibu jari bergerak berlebihan 1. Ibu jari dan jari lain bergerak berlebihan Lebihan pergerakan tangan KIRI 36 4. Pergelangan tangan atau atas lengan kekal tidak bergerak ketika ketukan 2. Kadang-kadang (sekali dua) pergerakan pergelangan tangan atau atas lengan untuk ‘membantu’ ketukan 1. Kerap (tiga kali atau lebih) pergerakan pergelangan tangan atau atas lengan untuk ‘membantu’ ketukan D Kesempurnaan jarak 4. Jari telunjuk menyempurnakan jarak ketukan dari lantai ke ketinggian gelang getah 2. Kadang-kadang (sekali dua) pergerakan yang tidak lengkap antara lantai dan gelang getah 1. Kerap (tiga kali atau lebih)pergerakan yang tidak lengkap antara lantai dan gelang getah E Jumlah ketukan jari yang sempurna dalam sepuluh saat Jangan kira pergerakan yang tidak sempurna atau sentuhan yang disebabkan pergerakan pergelangan tangan atau lengan Jumlah 37 PROTOKOL PEMARKAHAN UJIAN ROD GELUNGSOR (Pemerhatian ketika pergerakan tangan kiri dan kanan) Jarak individu berdiri lebih kurang satu kaki dari rod gelungsur pada paras ketingian pinggang. KANAN A Pergerakan henjutan-impulsif (pertukaran kadar kelajuan) 4. Pergerakan lunjuran yang sekata dan berterusan 2. Pertukaran pergerakan penyepit gelungsur; pertukaran kadar kelajuan yang ketara 1. Pertukaran pergerakan penyepit gelungsur; pertukaran kadar kelajuan yang ketara disertai dengan pergerakan berciri henjutan dan erotan B Ganguan 4. Lakuan tugasan tanpa ganguan (mata fokus pada penyepit rod ketika tugasan gelungsuran) 2. Ganguan dengan rangsangan luar (mata bergerak dari fokus sekali ketika tugasan gelungsuran) 1. Ganguan dengan rangsangan luar (mata bergerak dari fokus dua kali atau lebih ketika tugasan gelungsuran) C Pemindahan kepala-badan 4. Kepala dan badan kekal sementara mata mengikuti penyepit gelungsor; pergerakan mata selari dengan pergerakan penyepit gelungsur 2. Turutan pergerakan mata yang terhad dengan mengerakan kepala atau mengubah kedudukan badan sedikit untuk mengikuti pergerakan penyepit gelungsur 1. Pergerakan badan ketika mengikuti pergerakan penyepit rod; badan atau kepala;juga mata bergerak melebihi garisan tengah badan D Pergerakan badan berlebihan 4. Postur badan rehat dan kekal, pergerakan hanya pada tangan yang melakukan tugasan 2. Pergerakan berlebihan pada tangan dan kaki sekali ketika melakukan tugasan 1. Pergerakan berlebihan pada tangan dan kaki dua kali atau KIRI 38 lebih ketika melakukan tugasan E Kelajuan pergerakan (sehingga 30 saat). Rekodkan masa yang diambil untuk mengerakkan penyepit gelungsor ke hujung rod. Skor maksima untuk setiap tangan ialah 30 saat. Apabila kelajuan pergerakan adalah lima saat atau kurang, rekodkan skor “1”untuk setiap pemerhatian pergerakan di atas (A, B, C dan D). Jumlah 39 UJIAN IIMBANGAN DAN KOORDINASI PERGERAKAN (Balance And Movement Coordination Test – BMC Test) Ujian 1: Imbangan satu kaki dengan kedua tangan ditinggikan di atas kepala Objektif: Untuk mengukur imbangan statik pelaku berdiri di atas satu kaki sementara tangan memegang kayu rod/pembaris di atas kepala. Imbangan ini dilakukan untuk setiap kaki ketika mata terbuka dan tertutup. Alatan dan Material: Jam randik, pembaris 30sm, dan lantai yang rata dan kukuh. Prosedur: Tangan tegak di atas kepala dan memegang pembaris pada jarak seluas bahu. Berdiri di atas satu kaki dan angkat satu kaki pada sudut lebih kurang 60 hingga 90 darjah. Dengan mata terbuka, kekalkan imbangan selama yang boleh sehingga diberitahu untuk berhenti. Ulangi aktiviti yang sama dengan menukar kaki sokongan. Ujian ini diikuti dengan imbangan untuk setiap belah kaki dengan mata tertutup. Hentikan masa apabila pelaku melompat, mengelungsur, mengubah kaki imbangan, kaki yang diangkat menyentuh lantai, tangan terlepas ketika memegang pembaris, atau selepas pelaku dapat mengekalkan imbangan sehingga 60 saat. Sekiranya percubaan pertama kurang dari 10 saat, ulangi percubaan dan masa terbaik dikira sebagai skor. Arahan: “Apabila bersedia, angkat sebelah kaki anda dan imbang badan anda selama yang boleh ketika tangan berada tegak di atas kepala.” Pemarkahan: Rekodkan masa dalam saat. Jumlah skor dikira dari jumlah masa imbangan dalam saat untuk setiap kaki ketika mata terbuka dan tertutup. Mata terbuka Mata tertutup Jumlah (saat) Kaki kiri Kaki kanan Jumlah Ujian 2: Imbangan dinamik – Lompat sisi Objektif: Untuk mengukur imbangan dinamik pelaku ketika melompat sisi. Alatan dan material: Jam randik, pita penanda untuk menanda satu garisan tegak di atas lantai Prosedur: Pelaku berdiri dengan kedua-dua belah kaki berada di sisi pita penanda garisan tegak di atas lantai. Pada arahan “mula”, pelaku melompat sisi ke kiri dan kanan penanda garisan tegak dalam tempoh 10 saat dengan kedua-dua belah kaki sepantas yang boleh. Pelaku mestilah melompat dengan kedua-dua belah kaki. Lompatan dengan sebelah kaki adalah tidak dibenarkan (Sila lihat Gambarajah 1). 40 Pemarkahan: Jumlah lompatan ketika melompat dengan kedua-dua belah kaki dalam masa 10 saat direkodkan. Lompatan yang dilakukan dengan hanya menggunakan sebelah kaki atau lompatan yang menyentuh garisan adalah tidak dikira. Ujian Imbangan Dinamik Jumlah Lompatan lompatan sisi Gambarajah 1: Ilustrasi Ujian Imbangan Dinamik Ujian 3: Lari ulangalik – dengan objek dan tanpa objek. Objektif: Untuk mengukur keupayaan pelaku mengkoordinasi dan mengawal pergerakan badan disebabkan oleh perubahan arah pergerakan. Alatan dan material: Jam randik, tali penanda untuk menanda dua garisan selari sejauh 5 m, dua blok kayu 5 x 5 x 10 cm yang diletakkan di belakang garisan penamat. Prosedur: Tugasan 1: Pelaku berdiri dibelakang garisan mula. Pada arahan “mula”, pelaku lari ke arah blok kayu di garisan penamat, dengan satu kaki menyentuh garisan luar, ambil kayu blok, dan lari semula ke garisan mula dan letakkan blok kayu di belakang garisan. Sekali lagi, pelaku lari dan ulangi prosess yang sama seperti di atas dan akhirnya lari sepantas yang boleh ke garisan penamat (Sila lihat Gambarajah 2). Tugasan 2: Ulangi larian seperti yang diterangkan di atas tanpa mengambil apa-apa objek dengan rehat dibenarkan diantara tugasan. Pemarkahan: Tempoh masa yang digunakan dalam saat 41 Tugasan 1 Tugasan 2 Saat Garisan penamat 1 2 3 garisan mula Gambarajah 2: Ilustrasi Ujian Lari Ulang Alik Ujian 4: Lompatan satu kaki – setempat dan kepantasan Objektif: Untuk mengukur keupayaan pelaku mengkoordinasi dan mengawal pergerakan badan disebabkan oleh perubahan arah pergerakan. Alatan dan material: Jam randik, 2 kon, pita penanda Prosedur: Tugasan 1: Lompat satu kaki setempat – perlaku melompat berterusan dengan satu kaki sebanyak yang boleh dalam kawasan seluas 50 sm persegi dalam masa 10 saat. Kira setiap lompatan dan berhenti mengira sekiranya mana-mana bahagian kaki memijak atau terkeluar dari garisan atau pelaku berhenti melompat. Ulangi tugasan untuk kaki yang satu lagi. Tugasan 2: Melompat untuk kepantasan –pelaku berdiri di belakang garisan mula. Pada arahan ‘mula’ pelaku melompat dengan satu kaki ke garisan penamat (jarak 10 m) sepantas yang boleh. Hentikan masa apabila kaki lompatan mencecah garisan penamat. Ulangi tugasan untuk kaki yang satu lagi dengan rehat diberikan antara tugasan. Pemarkahan: Tugasan 1: Jumlah bilangan lompatan dalam masa yang diberikan. Tugasan 2: Masa yang diperlukan untuk menyempurnakan tugasan. Kaki kiri Kaki kanan Jumlah 42 Tugasan 1 (bilangan lompatan) Tugasan 2 (saat) Ujian 5: Larian zig-zag – arah kiri dan kanan Objektif: Untuk mengukur keupayaan pelaku mengkoordinasi dan mengawal pergerakan badan disebabkan oleh perubahan arah pergerakan. Alatan dan material: Jam randik, 5 kon. Prosedur: Letakkan lima kon dalam satu garisan lurus dengan jarak 1.5 m antara kon (lihat Gambarajah 3a dan 3b). Pelaku berdiri di belakang garisan mula. Pada arahan ‘mula’, pelaku lari ke kiri kon pertama, kemudian ke kanan kon kedua dan seterusnya secara selang-seli dan selepas kon ke lima, pusing dan ulangi larian selang-seli di antara kon hingga ke garisan penamat sepantas yang boleh. Rekodkan masa untuk menyempurnakan tugasan dalam saat. Untuk tugasan kedua, ulangi tugasan pertama tadi dari garisan mula yang lain (untuk mengubah arah larian). Gambarajah 3a adalah pergerakan bermula dari sebelah kanan peserta manakala Gambarajah 3b adalah pergerakan bermula dari sebelah kiri peserta. Pemarkahan: Masa dalam saat Arah kanan Arah kiri Larian Zig-zag (saat) 3a 3b Arah kiri Arah kanan 10 meter garisan mula/penamat Gambarajah 3: Ilustrasi Ujian Lari Zigzag garisan mula/penamat 43 Ujian 6: Lompat Kudron –berbeza arah Objektif: Untuk mengukur keupayaan pelaku mengkoordinasi dan mengawal pergerakan badan disebabkan oleh perubahan arah pergerakan. Alatan dan material: Jam randik, pita penanda Prosedur: Bentukan dua garisan melintang di atas lantai (lihat Gambarajah 4a dan 4b). Pelaku berdiri di posisi mula. Pada arahan “mula”, pelaku melompat dengan kedua-dua belah kaki ke petak kudron 1, 2, 3 dan 4 dan kembali ke petak 1, mengikut urutan. Pelaku meneruskan lompatan sehingga arahan berhenti. Kira jumlah lompatan. Untuk tugasan kedua, ulangi lompatan dari garisan mula dengan urutan lompatan pada arah yang berbeza (Lihat Gambarajah 4b). Pemarkahan: Skor adalah jumlah bilangan kaki mendarat di petak kudron yang betul dalam 10 saat. Tolak separuh (0.5) mata setiap kali kaki mendarat di atas atau terkeluar dari garisan. Skor terbaik di kira sebagai skor untuk ujian ini. Percubaan 1 Percubaan 2 Percubaan terbaik Jumlah kaki Jumlah Jumlah kaki Jumlah mendarat kesilapan mendarat kesilapan dengan betul dengan betul Arah A Arah B Gambarajah 4a – Arah A Gambarajah 4b – Arah B 3 2 2 3 1 4 4 1 Mula Gambarajah 4: Illustrasi Ujian Lompat Kudron Mula 44 BATTERI UJIAN UNTUK KENALPASTI BAKAT –PRESTASI MOTOR (Australian Talent Identification Test – AIS Test) Ujian 1: Baling / Lontar Bola Keranjang Tujuan : Tugasan lontar bola keranjang di bentuk untuk mengukur kekuatan bahagian atas badan. Alatan: Bola keranjang saiz 7, pita ukur 15 meter Prosedur: 1. Pelajar duduk dengan kaki melunjur ke hadapan manakala punggung, belakang badan dan kepala bersandar ke dinding. 2. Pelajar membuat hantaran bola paras dada ke hadapan sejauh yang boleh. Hantaran sebelah tangan atau hantaran paras bahu adalah tidak dibenarkan. 3. Pastikan pelajar mengekalkan kepala, bahu dan punggung bersentuhan dengan dinding ketika fasa lajak dan bola di baling hanya menggunakan otot tangan dan bahu. 4. Benarkan dua percubaan untuk setiap pelajar. Pemarkahan: Rekodkan jarak balingan terjauh yang menghampiri 5cm (ukur dari tempat jatuhnya bola pada lantunan pertama) Percubaan Jarak 1 2 Skor terbaik: ___________ Ujian 2: Lompat Menegak Tujuan: untuk mengukur keupayaan melompat pada arah menegak. Alatan: Serbuk kapur (bedak atau tepung juga boleh digunakan), dinding belapis dengan ukuran ketinggian dari 150 hingga 350 cm (tepat untuk 1 cm) Prosedur: 1. Pelajar mencelupkan hujung jari tangan dominan ke dalam serbuk kapur. 45 2. Tangan yang tidak digunakan diletakkan di pinggul. 3. Pelajar berdiri di sebelah sisi dominan berhampiran dengan dinding berlapis dengan tangan tegak ke atas dan menyentuh dinding berlapis dengan jari tengah untuk memberi kesan pada titik tertinggi. Kaki pelajar berkeadaan rata menyentuh lantai dan tangan ditegakkan setinggi yang boleh. Rekodkan titik yang ditanda pada 1 sm yang terhampir (Titik A). 4. Tangan pelajar berkedudukan tetap seperti di atas (tangan dominan diangkat tegak dan tangan tidak dominan diletakkan di atas pinggang) ketika pelajar mencangkung. Pelajar boleh memilih ketinggian cangkungan dan dibenarkan ‘menghenjut’ sekiranya perlu. Pelajar tidak dibenerkan untuk menghayun tangan untuk menambah momentum. 5. Pelajar melompat ke atas dari posisi ini dengan tangan ditegakkan ke atas untuk menyentuh dinding pada paras tertinggi yang boleh (Titik B). 6. Benarkan dua percubaan untuk setiap pelajar. Pemarkahan: Rekodkan sentuhan tertinggi ketika berdiri (titik A) dalam sentimeter terhampir. Rekodkan ketinggian yang di tanda oleh jari ketika lompatan (titik B). Tolak titik B dengan titik A untuk memperolehi jarak lompatan menegak dalam sentimeter. Percubaan Titik A Titik B Skor (titik B- titik A) 1 2 Skor terbaik: ___________ Ujian 3: 40 Meter Pecut Tujuan: Untuk mengukur keupayaan pecutan Alatan: Jam randik, kon (10), 40m trek larian – tegak dan sama rata. Sekiranya menggunakan padang rumput, pastikan ia kering. Prosedur: 1. Tanda trek larian 40 meter dengan meletakkan skitel/kon pada jarak setiap10 meter antara satu dengan yang lain. Pelajar bermula dengan posisi berdiri dengan kaki hadapan berada di atas garisan. 2. Penjaga masa mestilah berdiri di garisan penamat dengan satu tangan dinaikkan tinggi dan memberikan arahan ‘sedia’ dan menurunkan tangan secepat mungkin sebagai tanda permulaan 46 larian (tidak perlu memanggil mula). Pada masa tangan diturunkan, penguji memulakan masa jam randik yang dipegang oleh tangan sebelah lagi. 3. Berhentikan masa jam randik apabila badan pelajar melepasi garisan penamat. Galakkan pelajar untuk berlari sepantas yang boleh. 4. Benarkan dua percubaan untuk setiap pelajar. Pemarkahan: Rekodkan masa yang diambil pada percubaan yang terbaik pada 0.1 saat yang terhampir Percubaan Masa (saat) 1 2 Percubaan terbaik: ___________ Ujian 4: Larian Ulang-Alik- Ujian Kecergasan Pelbagai Peringkat Tujuan: Ujian lari ulang alik (ujian kecergasan pelbagai peringkat) digunakan untuk mengukur kecergasan aerobik. Alatan: Keset/CD untuk larian ulang alik, radio kaset/pemain cakera padat , pita penanda, permukaan rata berukuran 20 m dan bertanda, jam randik, kon (4) dan borang skor lari ulang-alik. Prosedur: 1. Periksa kepantasan kaset dengan menggunakan kalibrasi satu minit dan ubahsuaikan jarak larian jika perlu (diterangkan dalam keset dan manual ujian). 2. Ukur jarak 20 m dan tanda dengan pita penanda dan kon. 3. Mainkan pita kaset. Arahkan pelajar untuk berlari kearah bertentangan dan letakkan satu kaki dibelakang garisan untuk menunggu bunyi ‘beep’. Sekiranya pelajar tiba awal dari bunyi, pusing dan tunggu sehingga bunyi ‘beep’ dan lari ke garisan bertentangan dalam masa yang ditetapkan dan tunggu untuk bunyi seterusnya. 4. Di setiap penghujung minit, jarak masa antara beep berkurangan bermakna kepantasan larian meningkat secara berperingkat-peringkat. 5. Pastikan pelajar sampai ke garisan setiap masa dan tidak berpusing sebelum garisan. Ingatkan pelajar untuk sampai ke garisan dan berpusing berbanding lari dan berpusing yang mana ini akan mengambil masa yang lebih panjang. 47 6. Setiap pelajar meneruskan larian selama yang mampu mengikut bunyi/masa yang ditetapkan di dalam kaset. Pelajar terkeluar dari larian apabila pelajar ketingalan dua tapak ke garisan dari bunyi ‘beep’ sebanyak dua kali. Pemarkahan: Rekod tahap terakhir dan peringkat larian ulang alik yang berjaya disempurnakan. Tahap terakhir dan peringkat larian ulang alik ___________:_________________ 48 APPENDIX E 49 50 51 52 53 APPENDIX F A Brief Description of Test Administration Procedure and Score Sheets McCarron Assessment of Neuromuscular Development (1982) Test This section provides a brief description of the McCarron Assessment of Neuromuscular Development (MAND) test administration. A more comprehensive description of the test protocols is illustrated in the test manual. McCarron Assessment of Neuromuscular Development (MAND) consists of ten types of motor tasks. Five tasks are categories under Fine Motor Tasks and the other five tasks are categories under Gross Motor Tasks. Below is the list of the tasks: Fine Motor Tasks Gross Motor Tasks Beads in box Hand strength Beads on rod Finger-nose-finger movements Finger tapping Jumping Nut and bolt Heel-toe tandem walking Rod Slide Standing on one foot FINE MOTOR TASKS 1. Beads in Box This task requires the participant to move beads individually from one full box to an empty box (standard box) with one hand as fast as possible in 30 seconds. The tester demonstrates the tasks and gives the instructions to the participant. Repeat the procedure with the other hand. The participant can have an initial practice if necessary. Instructions: 1. “With your right hand, take one bead at a time from the full box and put it in the empty box. Go as fast as you can until I tell you to stop. Remember, take only one bead at a time. If you drop a bead, just let it go and keep on taking beads from the box.” 2. “With your left hand, take one bead at a time from the full box and put it in the empty box. Go as fast as you can until I tell you to stop. Remember, take only one bead at a time. If you drop a bead, just let it go and keep on taking beads from the box.” 54 Record only the number of beads that placed into the empty box individually in the time given. The score for this task is the total of the number of beads correctly transferred by both hands. 2. Beads on Rod In this task, the participant is required to thread the wooden cylinders beads into a rod. The nonpreferred hand holds the bottom of the rod firmly while the preferred hand places the beads individually as fast as possible on the rod in 30 seconds. Both hands should not rest on the table and free to move to position the beads. Repeat the procedure with the eyes closed. The participant can have an initial practice if necessary. Instructions: “Take one bead at a time and place it on the rod like this. Go as fast as you can until I tell you to stop. Be sure to hold the rod with your arms held a little away from your body.” Record the number of beads that placed on the rod individually in the time given. The score for this task is the total of the number of beads correctly transferred with eyes open and closed. 3. Finger Tapping The participant is required to tap index finger up and down in 10 s. The index finger must touch a rubber band when moved upward and touch the wooden board when moved downward. The rubber band should be at the level of index finger when the index finger is parallel to the platform. Repeat the procedure with the other hand. The participant can have an initial practice if necessary. Instructions: “Make a fist, but keep your thumb and index finger out. Now move your index finger up and down so it touches the board and then the rubber band. Do this as fast as you can. Move only the index finger.” Observe and record the motor behaviours (tapping rhythm, extraneous hand movements, overflow of arm movement and inconsistent complete finger tapping) and record the number of taps in the protocol sheets. The score for this task is the total of the number of the correct taps and observational ratings for both hands. 4. Nut and Bolt In this task, the participant is required to turn a large set of bolt into a nut as quickly as possible. The preferred hand that hold the bolt does the turning while the non-preferred hand that hold the nut is remain stationary. Both hands are at front without resting on the table or lap. Repeat the procedure with the small set of bolt into the nut. Instructions: “Hold the nut in this hand (non preferred) and turn the bolt (with preferred hand) into the nut. Turn the bolt as fast as you can and turn it all the way down.” 55 Individual task score is derived by subtracting the time required (in seconds) to completely turn the bolt into the nut from a score of 100. Record the scores by summing those for the two different sizes. 5. Rod slide This task requires the participant to continuously move a peg to the body as slowly as possible on the slide apparatus by using the hand and arm muscle. The participant is in standing position to perform the task with the apparatus at the waist level and approximately 30 cm away. The task is performed by both hands, left to right by the left hand and right to left by right hand. Instructions: “Thus far, you have been asked to do the motor tasks as fast as you can. This time, we are going to do something different. I want you to do this task as slowly as you can. Remember, the slower, the better. Move the pegs as slowly as you can, like this.” Record the time required to move the peg on the rod slide between the two ends of the apparatus. The participant may take longer time to complete the task as the slower the performance the better the score. However a maximum score of 30 seconds for each hand is allowed. Behavioural movement rating score of rate of movement, distractibility, head-body shifting, and extraneous body movements are also included. Sum both right and left hand score to get the total score for this task. GROSS MOTOR TASKS 1. Hand Strength This task requires the participant to holds the dynamometer with the arm out straight in front at shoulder level and squeeze the dynamometer as hard as possible. Each hand has two trials and alternating between trials. The best of two trials for each hand is recorded in kilograms. Instructions: “Squeeze the handle as hard as you can.” 2. Finger-Nose-Finger Movements In this task, the participant is required to touch his/her index finger on the tip of extended finger of the other hand and move to contact the tip of nose in10 seconds interval or approximately five nose contacts. The subject repeat the task using both right and left hands for the movement with eyes open and eyes closed making this task consists of four trials. Instructions: “This is not a speed test; just relax and do the best you can. Put your left arm straight out in front of you and point your finger to the wall. Now point just your finger to the wall on the right. (The left index finger is at right angles to the arm and points to the right or working side of the body). With the index finger of the right hand, touch the tip of your nose and then the tip of the extended finger like this.” 56 Behavioural ratings of arm movement, index finger on the extended hand, contact points, bending of elbow and indenting are recorded. Total score is the sum of scores with eyes open and eyes closed. 3. Jumping The participant jumps for a maximum distance with both feet together behind the restraining line for this task. Qualitative behaviours that are spring of legs, use of arms, trunk balance, and landing are assessed. Total score is the sum of the distance jumped and rating observed behaviours. Instructions: “With both feet together, jump across the room as far as you can.” 4. Heel-Toe Walk In this task, the participant is required to walk forwards on a 10 feet straight line by placing the heel of the forward foot in front of the toes of the rear foot and vice versa for movement backwards. The participant is required to wear flat shoes, barefooted or in stocking to perform the tasks and hands resting on the hips. Instructions: 1. Forward “Relax and do this task as carefully as you can. Put both your hands on your hips and walk on the line placing your heel directly in front of your toes, touching heel to toe on each step. Start here (one end of the tape) and walk all the way to the other end. 2. Backward “This time, walk backwards. Keep both hands on your hips and walk on the line placing your toe directly behind the heel, touching toe to heel on each step.” Behavioural movement of arm, feet, heel toe distance, progression and feet placement are observed, rated and recorded. Total score is the sum of the forward and backward walk. 5. Standing On One Foot The participant is required to keep balance while stand on one foot for a maximum period of 30 s. The participants are allowed to move their arms to maintain balance. Trials are conducted for both right and left legs with eyes opened and closed. Start the time once one leg is lifted off the floor and stop when the participant begins to hop, or either the lifted leg or hands touch the floor. A second trial will be given to the participant if participant unable to maintain the balance for more than 10 s. Instructions: 1. Eyes open “Stand on one foot as long as you can or until I tell you to stop.” 2. Eyes closed “This time, stand on one foot with your eyes closed. Remember, you must keep your eyes closed tight.” Record the time of balance in seconds. The total score is the sum of time of left and right legs balance with eyes open and closed. 57 McCarron (MAND) Assessment of Neuromuscular Development Score Sheet NDI __________ NAME : ________________________________________ DATE : _____________ DATE OF BIRTH : ____________________ AGE OF TESTING : _____________ SEX : Male / Female PREFERRED HAND: Right / Left PREFERRED LEG: Right / Left HEIGHT : _____ WEIGHT : ______DIAGNOSIS: _____________________________ BEADS IN BOX Right ____ Left ____ (number placed in Total Scaled score _____ _____ 30 seconds) BEADS ON ROD Eyes Eyes Total Scaled score (use cylinders only Open ____ Closed ____ _____ _____ Right ____ Left ____ Total Scaled score _____ _____ – number placed in 30 seconds) FINGER TAPPING (use score sheet) NUT BOLT Large Small Total Scaled score (number of 100 - ___ = ____ 100 - ___ = ____ _____ _____ seconds to complete tasks) ROD SLIDE (use Scaled score score sheet) _____ GRIP STRENGTH Right ____ (best of two trials with each hands) Left ____ Sub Total _____ FINE MOTOR AVERAGE _____ Total ____ Scaled score _____ 58 FINGER-NOSE-FINGER (use score sheet) Eyes Eyes open ____ Closed ____ Total ____ _____ JUMPING (use Total ____ score sheet) HEEL-TOE Scaled score Scaled score _____ Forward ___ Backward___ Total ____ WALK (use score Scaled score _____ sheet) ONE FOOT STAND (number of seconds up to 30) Eyes open Right ____ Left ____ Total _____ Eyes Closed Right ____ Left ____ Total _____ Total _____ Scaled score _____ Sub Total _____ GROSS MOTOR AVERAGE _____ OVERALL MOTOR AVERAGE _____ 59 MAND SCORE SHEET NAME : ________________________________ PROTOCOL SHEET FINGER TAPPING RIGHT LEFT A. Rhythm ________ ________ B. Extraneous hand movements ________ ________ C. Overflow of movement in arm ________ ________ D. Distance complete ________ ________ E. Number of taps ________ ________ ________ ________ RIGHT LEFT A. Change in speed _______ ________ B. Distractibility _______ ________ C. Head-body shifting _______ ________ D. Extraneous body movement _______ ________ E. Time taken _______ ________ _______ ________ TOTAL ROD SLIDE TOTAL FINGER-NOSE-FINGER EYES OPEN RIGHT LEFT EYES CLOSED RIGHT LEFT A. Arm movement smooth _______ _______ _______ ________ B. Index finger steady _______ _______ _______ ________ C. Contact points _______ _______ _______ ________ D. Elbow bending _______ _______ _______ ________ E. Indenting _______ _______ _______ ________ TOTAL JUMPING _______ TOTAL ________ 60 JUMP 1 JUMP 2 JUMP 3 A. Spring _____ _____ _____ B. Use of arms _____ _____ _____ C. Trunk balance _____ _____ _____ D. Landing knees flexed _____ _____ _____ E. Distance landing _____ _____ _____ _____ _____ _____ TOTAL HEEL-TOE WALK FORWARD BACKWARD A. Arm position _______ ________ B. Feet on tape _______ ________ C. Heel to toe distance _______ ________ D. Progression smooth _______ ________ E. Parallel placement of feet _______ ________ _______ ________ TOTAL PROTOCOL FOR SCORING FINGER-NOSE FINGER (Allow a 10 second interval to observe each trial) A Arm movement 4. Smooth, direct arm movement 2. Somewhat irregular or wavery arm movement 1. B Confused and jerky arm movement Index finger on the extended hand 4. Held steady 2. 1. Slight tremor or swaying Marked termor or swaying EYES OPEN EYES CLOSED Right Right Left Left 61 C Contact point 4. Contact point at tip of nose and tip of extended index finger 2. Missed contact point at either tip of nose or tip of index finger 1. Missed contact points at both tip of nose and tip of index finger D E Bending of elbow (gradual movement inward) 4. Holds arm fully extended 2. Slight bend at elbow (less than 30º) 1. Noted bend at elbow (more than 30º) Indenting 4. Lightly touches tip of extended index finger and end of nose 2. Noted pushing of tip of extended index finger or presses in end of nose once or twice 1. Noted pushing in of tip of extended index finger or presses in the end of nose three or more times Totals 62 PROTOCOL FOR SCORING JUMPING: (Body movements are rated according to an overall impression of typical performance as observed during all three jumps) A B C Spring 4. An even spring into the air from both feet 2. An awkward spring into the air, predominant use of one leg to spring 1. Clumsy spring; limited ability to spring off the floor Use of arms 4. Arms assist with slight spring forward and return to sides 2. Arms move limpy with limited assistance 1. Arms held rigidly; are not used to assist Trunk balance 4. Landing stable; centre of gravity midline (remains in place) 2. Landing unstable but able to regain balance 1. Landing unstable; steps backward or forward or uses hands to prevent falling D Landing with knees flexed 4. Smooth landing on both feet simultaneously with slight bending of knees to absorb the fall E 2. Somewhat stiff landing; limited use of knee bend 1. Stiff landing with stiff knees; jars the body when landing Distance of jump The distance scored recorded in the farthest jump of the three attempts Total 63 PROTOCOL FOR SCORING HEEL-TOE WALK (Individual walks a distance of 10 feet) FORWARD A B Arms/body sway 4. Both hands remain on hips 2. Removed one hand from hip 1. Removed both hands from hips Feet 4. Retained both feet on tape line 2. Foot altered from line once or twice (when less than half the tape is covered, the foot is considered off) 1. C Foot altered from line three or more times Heel to toe distance 4. Heel positioned within one inch of the toe 2. Heel positioned greater than one inch from toe once or twice 1. Heel positioned greater than one inch from toe three or more times D Progression 4. Smooth forward walk 2. Slight pauses in forward movement 1. Shifting of weight backward and forward while walking E Parallel placement 4. Both feet kept parallel to the tape line 2. Steps correctly, but then rotates foot to an angle (20º or more) with the line 1. Steps at an angle (20º or more) with the line BACKWARD 64 Totals Parallel Placement Rotation 20º 65 FINGER TAPPING SCORING PROTOCOL: (Observe for 10s interval with each hand) RIGHT A B C Rhythm of tapping 4. Even, consistent rhythm of tapping 2. 1-2 disruptions of rhythm, but regains consistent tapping 1. Erratic, non-rhythmic tapping Extraneous hand movements 4. Moves only the index finger, fist remain closed 2. Extraneous movement of thumb 1. Extraneous movement of thumb and other fingers Overflow of movement in arm 4. Wrist or forearm remains stationary while tapping 2. Occasional (1-2) movement of wrist or forearm to “assist” tapping 1. Frequent (≥3) movement of wrist or forearm to “assist” tapping D Complete distance 4. Index finger move the complete distance between base and suspended rubber band 2. Occasional (once or twice) incomplete movement between base and rubber band 1. Frequent (three or more) incomplete movements of the index finger between base and rubber band E Number of complete finger taps in ten seconds Do not count incomplete movements or contacts made by movements of wrist or forearm Total LEFT 66 PROTOCOL FOR SCORING ROD SLIDE (Observations during movement of the right and left hands) The individual stands approximately one foot away from the rod slide and the height of the rod is at waist level. RIGHT A Impulsive-jerky movements (change in rate of speed) 4. Continuous even slide 2. Changes in slide motion; obvious deviation in speed 1. Changes in slide motion; obvious deviation in speed with erratic and impulsive movement B Distractibility 4. Attended to ask without distraction (eyes remains focused on bead during slide) 2. Distracted by extraneous stimuli (eyes shifted from focus once during slide) 1. Distracted by extraneous stimuli (eyes shifted from focus two or more times during slide) C Head-body shifting 4. Head and body remain stationary while the eye track the bead; the movement of the eyes parallels the movement of the bead 2. Limited tracking movement of eyes with turning of head or partial shifting of body to follow the bead 1. Simultaneous shifting of body while tracking the bead; the body or head, rather than the eyes, shifts past the midline D Extraneous body movements 4. Body posture relaxed and stationary; moves only the arm performing the task LEFT 67 2. Extraneous movements of other arm and legs once during the task 1. Extraneous movements of other arm and legs two or more times during the task E Speed of movement (up to 30 seconds) Record the time taken to move the bead the full distance across the rod. The maximum possible score for each hand is 30 seconds. When the speed of movement is 5 seconds or less, record a score of “1” for each of the behavioural observations above (A, B, C and D). Totals 68 Balance and Movement Coordination (BMC) Test BMC - MOVEMENT CONTROL AND COORDINATION TEST Test 1: One foot balance with elevated hand or arms above head. Objective: To measure static balance of the performer supported on one foot while hands holding a rod above the head. The balance will be done on each foot with eyes open and eyes closed. Equipment and Materials: Stopwatch, 30cm ruler and firm level surface. Procedures: Hands straight above head and holding ruler about shoulder width. Stand on one foot and lift up the other foot to make an angle at the knee approximately 60 to 90 degrees. With eyes open, maintain the balance as long as possible until asked to stop. Then, repeat on the other foot. Following this, the test is repeated on each leg with eyes closed. Start timing the trial when the performer lifts up the free foot. Stop timing when the performer hops or slides or repositions the supporting foot, or the free foot touches the floor, or one of the hands slip off the ruler, or after the performer maintains the balance for 60 seconds. If a trial lasts less than 10 seconds, it is repeated and the better score is taken. Instruction: When you are ready to start, lift your leg and balance for as long as you can keeping your hands stretched above your head. Scoring: Record the time in seconds. The total score is derived from sum of seconds of each foot able to balance with eyes opened and eyes closed. Eyes opened Left foot Right foot Total Eyes closed Total (seconds) 69 Test 2: Dynamic balance – sideways Objective: To measure the dynamic balance of the performer while jumping sideways. Equipment and Materials: Stopwatch, marking tape to mark a straight line on the floor. Procedures: Performer stands next to a straight line marking tape on the floor. With their legs together, the performer stands sideways next to the line. On the signal “go”, the performer jumps sideways back and forth in 10 seconds over the line with legs together as fast as she/he can. The performer should jump with both feet at the same time. Jumping with one leg is not allowed (See Figure 1). Scoring: Numbers of jumps in 10 seconds with both feet together. Do not count jumps with one leg or jumps that touch the line. Dynamic balance task Numbers of jumps Side jump Figure 1: Diagram of Dynamic Balance Test Test 3: Shuttle run - with object and without object. Objective: To measure the ability of the performer to coordinate and control body movements on changing directions. Equipment and Materials: Stopwatch, marking tape to mark two parallel lines 5m apart, and two blocks of wood 5 x 5 x 10 cm placed behind the line 5m from the starting line. 70 Procedures: Task 1: The performer stands behind the starting line. On the signal ‘go’, performer runs to the blocks at the other line and touches the ground on the far side of the line with one foot, picks up one of the blocks, and runs back to the starting line placing the block behind the line. The performer repeats the processes with the second block then run as fast as possible across the finishing line. (See Figure 2) Task 2: Repeats the run as describe above without picking up any object with rest allowed between tasks. Scoring: The length of time to complete the tasks is recorded in seconds. Task 1 Task 2 Seconds Finishing line 1 2 3 Starting line Figure 2: Diagram of Shuttle Run Test Test 4: Hop – stationary and speed. Objective: To measure the ability of the performer to coordinate and control body movement on changing directions. Equipment and Materials: Stopwatch, two cones, marking tape. 71 Procedures: Task 1: Stationary hop -performer hops continuously as many times as possible on one foot within a 50 cm marked squared in 10 seconds. Count each hop. Stop counting if any part of the foot either steps onto or protrudes over the line or if the performer stops hopping. Repeat the task with the other foot. Task 2: Hopping for speed – the performer stands behind the starting line. On the signal ‘go’, the performer hops to the other line (10-meter distance) as fast as she/he can. Stop the time when the hopping foot touches the finishing line. Repeat the task with the other foot with rest between tasks. Scoring: Task 1: The number of hops in time given. Task 2: The time in seconds to complete the tasks. Left foot Right foot Total Task 1 (number of hop) Task 2 (seconds) Test 5: Zig-zag run – right and left direction. Objective: To measure the ability of the performer to coordinate and control body movement on changing directions. Equipment and Materials: Stopwatch, Skittle/cones – 5 Procedures: Placed five skittle/cones in one straight line with 1.5m in between of each skittle/cones (see Figure 3). The performer stands behind the starting line. On the signal ‘go’, the performer runs to the left of first skittle, then to the right of second skittle, to the left of the third skittle, to the right of the fourth skittle, to the left of fifth skittle, then turns back and runs again to the left and right of the skittles alternately and runs to the finishing line as fast as she/he can. Time the run to complete the task in seconds. Repeat the task from different starting line (to change the run direction) - see Figure 3a and 3b. 72 Scoring: Time in seconds Right direction Left direction Zig-zag run (seconds) Figure 3a Figure 3b Left direction Right direction 10 meter start/finishing line start/finishing line Figure 3: Diagram of Zigzag Run Test Test 6: Quadrant jump – different directions Objective: To measure the ability of the performer to coordinate and control body movement by jumping in different directions. Equipment and Materials: Stopwatch, masking tape Procedures: Place two cross lines on hard surface (see Figure 4a and 4b). The performer stands on the start position. On the signal ‘go’, the performer jumps with both feet into quadrant 1, then into quadrant 2, into 3, into 4, and back to 1. Performer continues jumping until asked to stop. Count the jumping. Repeat the jumping in a different sequence (see Figure 4b). Two trials for each direction are given with rest between trials. Scoring: The score is the number of times the feet land in correct quadrants in 10 seconds. Deduct half (0.5) point each time performer lands on wrong quadrant or any part of the feet land on the line. The better score of the two trials is the test score. 73 Trial 1 Trial 2 Best trials Numbers of Numbers of Numbers of Numbers correct errors correct of errors landings landings Direction A Direction B Figure 4a Figure 4b 3 2 2 3 1 4 4 1 Start Figures 4a and 4b. Start Diagrams of the Quadrant Jump Test 74 TEST BATTERY IN TALENT IDENTIFICATION PROGRAM - MOTOR PERFORMANCE (Australia Sports Commission, 1998) Test 1: Basketball Throw Purpose: The basketball throw task is designed to measure upper body strength. Equipment: Size 7 basketball, 15 meter tape measure Procedures: 5. The student sits with their buttocks, back and head resting against a wall. Their legs rest on the floor horizontally in front of the body. 6. The student uses a two-handed chest pass to push the ball in the horizontal direction as far forward as possible. A one arm or shoulder pass is not allowed. 7. Ensure that the student keeps the head, shoulders and buttocks in contact with the wall as they follow through, and the ball is thrown only using the arm and shoulder muscles. 8. Allow two trials for each student. Scoring: Record the longest distance thrown to the nearest 5 cm (measure from the base of the ball where it makes contact with the ground on the first bounce). Trials Distance 1 2 Best score: ___________ Test 2: Vertical Jump Purpose: The vertical jump task measures the ability to spring in a vertical direction. Equipment: Powder chalk (talcum powder or flour is appropriate), Wall mounted board covering heights from 150 to 350 cm (accurate to 1 cm). 75 Procedures: 1. The student dips the fingertips of the preferred hand into the powder chalk. 2. The non-preferred hand is placed on the hip. 3. The student stands with the preferred side nearest the board and reaches upward with their arm closest to the wall and touches the board with their middle finger to leave a mark at the highest possible point. The feet should be flat on the floor and the arm/hand extended as high as possible. Record the position of this mark to the nearest 1 cm (Point A). 4. The student’s arms are to remain in the same position as above (the preferred arm is raised vertically and the non-preferred arm placed on the hip) as they go into a crouch. The student can choose the depth of crouch and is allowed to ‘bounce’ if desired. The student is not allowed to swing the arms to assist momentum. 5. The student then springs upward from this position to touch the wall at the highest possible point with the outstretched arm closest to the board (Point B). 6. Allow two trials for each student. Scoring: Record the reaching height to the nearest cm. Record the final height (to the nearest cm) the student jumped on the best trial. Subtract the reaching height from the vertical jump height to obtain the vertical jump distance in centimeters. Trials Point A Point B Score (Point B – Point A) 1 2 Best score: ___________ Test 3: 40 Metre Sprints Purpose: Speed is also important in sports requiring short bursts of activity at high intensity such as sprint running. Equipment: Stopwatch, Skittle/cones (10), 40 metre running track that is straight, level and placed cross-wind. If a grass surface is used ensure that it is dry. Procedures: 5. Mark a 40-meter running track with witches’ hats placed at 10-meter intervals. The student starts in a standing position with their front foot exactly on the line. 76 6. The timer should stand at the finish line with one arm held high, call ‘ready’ and then sweep down their arm quickly to start the student (do not call go). As the arm sweeps down the tester should simultaneously start the stopwatch which is held in the descending hand. 7. Stop the stopwatch when the student’s chest crosses the line. Emphasize to the student to run as quickly as possible. 8. Allow two trials for each student. Scoring: Record the time taken for the fastest trial to the nearest 0.1 of a second. Trials Time 1 2 Best score: ___________ Test 4: Shuttle Run – Multistage fitness test Purpose: The shuttle run (multistage fitness test) is used to assess aerobic fitness. Equipment: Cadence audio CD/tape for shuttle run ,Masking tape ,Cassette player, 20 m marked distance on a surface that is flat, even and slip resistant, Stopwatch, skittle/cone (4) and Shuttle run record form. Procedures: 1. Check the speed of the cassette player using the one minutes calibration period and adjust the running distance if necessary (this is described on the tape and in the tape manual). 2. Measure the 20 m distance and mark with tape and witches hats. 3. Start the cadence audio tape. Instruct the student to run to the opposite end and place one foot behind the line by the time the next beep sounds. If they arrive before the beep they should turn (pivot) and wait for the signal, then run to the opposite line to reach this in time for the next signal. 4. At the end of each minute the time interval between beeps is decreased, thereby running speed becomes progressively faster. 77 5. Ensure the student reaches the end line each time and does not turn short. Emphasize to the student to pivot and turn rather than run an arc which some tend to do (this takes more time). 6. Each student continues running for as long as possible until he/she can no longer keep up with the tape. The criterion for eliminating a student is two lengths in a row where he/she is more than two steps from the end. Scoring: Record the last level and shuttle the student successfully completed. Last Level and Shuttle: ___________ 78 APPENDIX G Table 1 Conversion of Summed Scaled Scores to NDI for Children - Ages ≥11 years NDI Summed NDI Scale 155 134 154 153 133 152 151 132 150 149 131 148 147 130 146 145 129 144 143 128 142 141 127 140 139 126 138 137 125 136 135 124 123 132 131 130 129 121 128 127 120 Summed NDI Scale Summed Scale 126 119 97 94 68 51-52 125 118 96 93 67 49-50 124 117 95 92 66 47-48 123 116 94 91 65 45-46 122 115 93 89-90 64 43-44 121 114 92 88 63 41-42 120 113 91 87 62 39-40 119 112 90 86 61 37-38 118 111 89 85 60 35-36 117 110 88 84 59 33-34 87 83 58 31-32 116 115 109 86 82 57 29-30 114 108 85 81 56 27-28 113 107 84 80 55 25-26 112 106 83 79 54 23-24 111 105 82 78 53 21-22 110 104 81 77 52 19-20 109 103 80 75-76 51 18 108 102 79 73-74 50 17 78 71-72 49 15-16 106 101 77 69-70 48 13-14 105 100 76 67-68 47 12 75 65-66 46 11 74 63-64 45 10 73 61-62 44 8-9 104 103 122 NDI Scale 107 134 133 Summed 99 102 101 98 72 59-60 43 6-7 100 97 71 57-58 42 4-5 99 96 70 55-56 41 2-3 98 95 69 53-54 40 1 79 TABLE 2 MAND Table of Norms for Normal Children AGE 12-0 Scale Beads Beads Finger Nut and Score Box Rod Tapping 20 65-66+ 31+ 19 64 18 Rod Slide Hand Finger Jumping Bolt Strength Nose 120+ 194+ 63-64+ 95+ 30 117-119 191-193 62 92-94 62-63 29 113-116 189-190 60-61 90-91 17 60-61 28 110-112 186-188 58-59 87-89 16 59 27 107-109 183-185 57 84-86 15 57-58 26 103-106 181-182 55-56 82-83 14 55-56 25 100-102 178-180 53-54 79-81 13 54 24 97-99 175-177 92 52 79-80 76-78 12 52-53 23 93-96 173-174 90-91 50-51 76-78 74-75 11 50-51 22 90-92 170-172 88-89 48-49 73-75 71-73 10 49 21 87-89 167-169 86-87 47 70-72 68-70 9 47-48 20 83-86 165-166 84-85 45-46 67-69 66-67 8 45-46 19 80-82 162-164 82-83 43-44 64-66 63-65 7 44 18 77-79 159-161 80-81 42 61-63 60-62 6 42-43 17 73-76 157-158 78-79 40-41 58-60 58-59 5 40-41 16 70-72 154-156 76-77 38-39 55-57 55-57 4 39 15 67-69 151-153 74-75 37 52-54 52-54 3 37-38 14 63-66 149-150 72-73 35-36 49-51 50-51 2 35-36 13 60-62 146-148 70-71 33-34 46-48 47-49 1 34 12 57-59 143-145 68-69 32 43-45 44-46 He 80 TABLE 3 MAND Table of Norms for Normal Children AGE 13-0 Scale Beads Beads Finger Nut and Score Box Rod Tapping 20 67+ 31 19 65-66 18 Rod Slide Hand Finger Jumping Bolt Strength Nose 130+ 196+ 87+ 94+ 30 126-129 193-195 83-86 92-93 64 29 122-125 191-192 80-82 80 89-91 17 62-63 28 118-121 188-190 76-79 79 87-88 16 60-61 27 114-117 185-187 72-75 78 85-86 15 59 26 110-113 183-184 92 69-71 77 82-84 14 57-58 26 106-109 180-182 91 65-68 77 80-81 13 55-56 25 102-105 177-179 90 61-64 76 78-79 12 54 24 98-101 175-176 89 58-60 75 75-77 11 52-53 23 94-97 172-174 88 54-57 74 73-74 10 50-51 22 90-93 169-171 87 50-53 73 71-72 9 49 21 86-89 167-168 86 47-49 72 68-70 8 47-48 20 82-85 164-166 85 43-46 71 66-67 7 45-46 19 78-81 161-163 84 39-42 70 64-65 6 44 18 74-77 159-160 83 36-38 69 61-63 5 42-43 18 70-73 156-158 82 32-35 68 59-60 4 40-41 17 66-69 153-155 81 28-31 67 57-58 3 39 16 62-65 151-152 80 25-27 66 54-56 2 37-38 15 58-61 148-151 79 21-24 65 52-53 1 35-36 14 54-57 145-147 78 17-20 64 50-51 He 3 3 3 2 81 TABLE 4 MAND Table of Norms for Normal Children AGE 14-0 Scale Beads Box Score Beads Finger Nut and Rod Rod Tapping Bolt Slide Hand Strength Finger Jumping Nose Male Female Male Fem 92 20 68+ 31 133+ 197+ 95+ 76+ 104+ 19 66-67 30 129-132 194-196 91-94 74-75 101-103 90 18 65 29 125-128 192-193 88-90 71-73 98-100 87 17 63-64 28 121-124 189-191 84-87 69-70 95-97 85 16 61-62 27 117-120 186-188 80-83 67-68 80 92-94 83 15 60 26 113-116 184-185 77-79 64-66 79 89-91 80 14 58-59 26 109-112 181-183 92 73-76 62-63 79 86-88 78 13 56-57 25 105-108 178-180 91 69-72 60-61 78 83-85 76 12 55 24 101-104 176-177 90 66-68 57-59 77 80-82 73 11 53-54 23 97-100 173-175 89 62-65 55-56 76 77-79 71 10 51-52 22 93-95 170-172 88 58-61 53-54 75 74-76 69 9 50 21 89-92 168-169 87 55-57 50-52 74 71-73 67 8 48-49 20 85-88 165-167 86 51-54 48-49 73 68-70 65 7 46-47 19 81-84 162-164 85 47-50 46-47 72 65-67 62 6 45 18 77-80 160-161 84 44-46 43-45 71 62-64 59 5 43-44 18 73-76 157-159 83 40-43 41-42 70 59-61 57 4 41-42 17 69-72 154-156 82 36-39 39-40 69 56-58 55 3 40 16 65-68 152-153 81 33-35 36-38 68 53-55 52 2 38-39 15 61-64 149-151 80 29-32 34-35 67 50-52 50 1 36-37 14 57-60 146-148 79 25-28 32-33 66 47-49 48 82 TABLE 5 MAND Table of Norms for Normal Children AGE 15-0 Scale Beads Beads Finger Nut and Rod Score Box Rod Tapping Bolt Slide Hand Strength Finger Jumpi Nose Male Female Male 20 72+ 31 136+ 107+ 79+ 99+ 19 70-71 30 132-135 103-106 77-78 97-98 18 68-69 30 128-131 99-102 74-76 95-96 17 66-67 29 124-127 197-199 95-98 72-73 92-94 16 64-65 28 120-123 193-196 91-94 70-71 90-91 15 62-63 27 116-119 190-192 87-90 67-69 87-89 14 60-61 26 112-115 186-189 83-86 65-66 85-86 13 58-59 25 108-111 182-185 92 79-82 63-64 80 83-84 12 56-57 25 104-107 179-181 91 75-78 60-62 79 80-82 11 54-55 24 100-103 175-178 90 71-74 58-59 78 78-79 10 52-53 23 96-99 171-174 89 67-70 56-57 77 76-77 9 50-51 22 92-95 168-170 88 64-66 53-55 76 73-75 8 48-49 21 88-91 164-167 87 59-63 51-52 75 71-72 7 46-47 20 84-87 160-163 87 55-58 49-50 74 69-70 6 44-45 20 80-83 157-159 86 51-54 46-48 73 66-67 5 42-43 19 76-79 153-156 85 47-50 44-45 73 64-65 4 40-41 18 72-75 149-152 84 43-46 42-43 72 62-63 3 38-39 17 68-71 146-148 83 39-42 39-41 71 59-61 2 36-37 16 64-67 142-145 82 35-38 37-38 70 57-58 1 34-35 15 60-63 138-141 81 31-34 35-36 69 55-56 83 TABLE 6 MAND Table of Norms for Normal Children AGE 16-0 Scale Beads Beads Finger Nut and Rod Score Box Rod Tapping Bolt Slide Hand Strength Finger Jumping Nose Male Female Male Fem 92 20 70+ 32 139+ 199 112+ 83+ 108+ 19 68-69 31 135-138 196-198 108-111 81-82 105-107 90 18 67 30 131-134 194-195 105-107 78-80 102-103 87 17 65-66 29 127-130 191-193 101-104 76-77 99-101 85 16 63-64 28 123-126 188-190 97-100 74-75 96-98 83 15 62 27 119-122 186-187 94-96 71-73 93-95 80 14 60-61 27 115-118 183-185 90-93 69-70 90-92 78 13 58-59 26 111-114 180-182 92 86-89 67-68 80 87-89 76 12 57 25 107-110 178-179 91 83-85 64-66 79 84-86 73 11 55-56 24 103-106 175-177 90 79-82 62-63 78 81-83 71 10 53-54 23 99-102 172-174 89 75-78 60-61 77 78-80 69 9 52 22 95-98 170-171 88 72-74 57-59 76 75-77 66 8 50-51 21 91-94 167-169 87 68-71 55-56 75 72-74 64 7 48-49 20 87-90 164-166 86 64-67 53-54 74 69-71 62 6 47 19 83-86 162-163 85 61-63 50-52 73 66-68 59 5 45-46 19 79-82 159-161 84 57-60 48-49 72 63-65 57 4 43-44 18 75-78 156-158 83 53-56 46-47 71 60-62 55 3 42 17 71-74 154-155 82 50-52 43-45 70 57-59 52 2 40-41 16 67-70 151-153 81 46-49 41-42 69 54-56 50 1 38-39 15 63-66 148-150 80 42-45 39-40 68 51-53 48 84 APPENDIX H Confirmatory Factor Analyses of The MAND In all confirmatory factor analyses, the motor skills were loaded on the appropriate factors, the measurement errors were not allowed to correlate, and the model was identified by fixing the factor variances to 1.00. Three overall fit indices suggested by Hoyle and Panter (1995) were then examined for the confirmatory models. 4.1.1. The MAND McCarron (1982) developed the MAND to assess fine and gross motor ability at a basic level. The instrument is primarily used to identify motor problems that underscore neurological dysfunction within individuals. Therefore, the two factor and four factor psychometric models were examined which were based upon the instrument development work of McCarron (1982). The first was a 2factor model that consisted of the fine and gross motor components originally derived by McCarron (1982). The second was a 4-factor model that McCarron (1982) reported for a sample of normal children aged 7 years. In all confirmatory factor analyses, the motor skills were loaded on the appropriate factors, the measurement errors were not allowed to correlate, and the model was identified by fixing the factor variances to 1.00. Three overall fit indices suggested by Hoyle and Panter (1995) were then examined for the confirmatory models. These indices included the chisquare, which is an absolute fit index that highlights lack of fit resulting from over-identifying restrictions placed upon the model. The Nonnormed Fit Index (NNFI) was also examined to obtain an estimate of the relative improvement per degree of freedom of the target model over a baseline model. Finally, the Comparative Fit Index (CFI) was examined to determine the relative reduction in lack of fit as estimated by the non-central chi-square of a target model to a baseline model. The confirmatory factor analysis of the 2-factor model of the MAND proposed by McCarron (1982) did not fit very well with the Malaysian Adolescent sample. Specifically, the 2-factor model differed significantly from the independence model (Chi-square = 53.94, Robust Chi-square = 51.75, df = 34, p < .027) and the other indices of model adequacy were poor. The observed goodness-of-fit (CFI = .87; Robust CFI = .88; NNFI = .83; Robust NNFI = .77) were substantially lower than would be desired. A standardised Root Mean Square Residual of .001 was also observed for the 2-factor model. Most of the 55 residuals were of an acceptable magnitude (90.90% z < |.1|). However, 9.10% of the residuals were greater than .2. The factor loadings averaged .382 and ranged from .139 to .691. From a total of 10 motor skills, 4 of these had a variable loading less than .40. The correlation between the two latent factors revealed a moderately low relationship (r = .405). 85 Confirmatory factor analysis of the four-factor model also suggested that this model was not a good approximation of the MAND data. Specifically, the four-factor model differed significantly from the independence model (Chi-square = 71.22, Robust Chi-square = 68.16, df = 29, p < .0001), and the other indices of model adequacy were also poor. The observed goodness-of-fit (CFI = .73; Robust CFI = .73; NNFI = .58; Robust NNFI = .41) was lower than would be desired. A standardised Root Mean Square Residual of .001 was also observed for the four-factor model. Of the 55 residuals, 85.46% were of an acceptable magnitude (z < |.1|). However, 14.54% were larger than .2. The factor loadings averaged .390 and ranged from .082 to .716. From a total of 10 motor skills, 8 had a variable loading less than .40. The correlations among the latent factors revealed moderate relationships for Factor 1 with Factors 2 (r = .413) and 4 (r = .599). Moderate relationships also were found for Factor 3 with Factors 2 (r = .672) and 4 (r = .679). There was a small correlation found between Factor 2 and Factor 4 (r = .235), and a substantial correlation between Factor 1 and Factor 3 (r = .887). In summary, the results for both factor models were unsatisfactory, thereby indicating that exploratory factor analysis was required. 86 APPENDIX I 4.3. 4.3.1. RESULTS: TESTING FOR MOTORIC ‘g’ – ALL PARTICIPANTS First-Order Factor Analysis A factor analysis was conducted on the normalised T-scores of the combined AIS+BMC. The oblique rotation (PROMAX) with kappa = 4 was selected, as this number gives better results for further higher-order factor analyses (Rummel, 1970). Three rotated factors were extracted that accounted for 53.2% of the variance. The eigenvalues, percent of variance, rotated factor loadings, and the intercorrelation matrix of the AIS+BMC items are presented in Table 10. Table 6. Correlations, Factors & Factor Loadings Underlying the AIS+BMC for All Participants. Factor 1 2 3 Eigenvalue 4.64 1.18 1.09 % of variance 35.70 9.08 8.41 Cumulative % 35.70 44.78 53.19 Test 1 2 3 4 5 6 7 8 9 10 11 12 13 1. Shuttle Run - .81 .65 .57 .38 .44 .32 .26 .34 .30 .27 .18 .32 2. Shuttle run/obj. - .59 .55 .34 .38 .27 .23 .31 .28 .22 .15 .27 3. Hopping speed - .58 .36 .49 .31 .24 .29 .28 .21 .22 .27 4. Zigzag run - .38 .44 .35 .31 .29 .27 .26 .17 .30 5. Multistage fitness test - .40 .23 .20 .22 .12 .22 .13 .20 6. 40m sprint 7. Dynamic balance 8. Hopping-in-square 9. Quadrant jump 10. Basketball throw 11. Vertical jump 12. One foot balance with eyes open 13. One foot balance with eyes closed Note. Loadings .50 and above are in bold. .906 .905 -.103 .812 .705 .102 .530 - .32 .24 .27 .18 .27 .22 .25 .528 .127 .156 - .43 .40 .20 .22 .18 .22 .810 .100 - .23 .20 .17 .15 .17 -.114 .792 - .21 .12 .15 .21 .544 - .21 .07 .10 .299 .388 -.334 - .09 .13 .264 .314 -.157 - .33 .800 - .198 .679 87 Factor One: The variables loaded on this factor were the shuttle run (.906), shuttle run with object, (.905), hopping speed, (.812), zigzag run, (.705), multistage fitness test (.530) and 40m sprint (.528). Factor Two: High loadings in this factor were the dynamic balance (.810), hopping-in-square (.792) and quadrant jump (.544). Factor Three: This factor had loadings on one foot balance with eyes open (.800), and one foot balance with eyes closed (.679). 4.3.2. Higher-Order Factor Analysis The higher-order factor analysis extracted one element and accounted for 55.9% of variance in the solution. The eigenvalues, percentage of variance and factor loadings from the higher-order analysis are presented in Table 11. Table 7. Higher-order Factor Analysis of the AIS+BMC for All Participants. Higher-Order Factor 1 Eigenvalue 1.68 % of variance 55.92 Factors Factor 1 Factor 2 1 2 3 - .49 .37 .821 - .30 .804 - .597 Factor 3 4.3.3. Discussion – All Participants First-Order Factor Analysis. There was a small variation in the underlying constructs of the AIS and BMC tests when analysed separately, and then compared with the underlying constructs found for the combined AIS+BMC. Specifically, the Anaerobic Power factor found in the factor analysis of the AIS disappeared as an entity in the combined AIS+BMC analyses. Two of the motor skills that made up anaerobic power (i.e., the 40m Sprint and the Multistage Fitness Test, [MSFT]) merged with the BMC construct named movement coordination. The remaining two motor skills that assessed anaerobic power from the AIS (i.e., the basketball throw and the vertical jump) did not exceed the cut-off point of .50 for inclusion on any factor found for the combined AIS+BMC. Subsequently, the remaining eleven motor skill tests loaded on to one of three factors and explained 53.2% of the variance. 88 The First Factor explained 35.7% of the variance. The variables that loaded on to this factor were the shuttle run, shuttle run with object, hopping speed, zigzag run, multistage fitness test and 40m sprint. The task analysis on the shuttle run, shuttle run with object, zigzag run and multistage fitness test items, indicated that these motor skills reflected an ability to change movement direction and the body position without loss of balance (Hilsendager, Strow & Ackerman, 1969). Hopping speed and 40m sprint also loaded on this factor, indicating that speed and strength were important components. Both motor skills are of a high intensity and require maximal rates of energy (Anshel, 1991; Bencke et al., 2002; Manning et al., 1988). However, hopping at speed requires both speed and strength, and an ability to maintain balance in a small base of support (Chelly & Denis, 2001; Haywood, 1993a). As a group then, the motor skills that were loaded not only require speed, balance, agility and characteristics related to coordination, they also require well timed and well balanced functioning of several muscles together for successful performance (Barrow, 1977). Given these considerations, factor one was labelled ‘movement coordination’. The Second Factor explained 9.08% of variance and consisted of dynamic balance, hopping-in-square and the quadrant jump. All of these tasks require balance and strength, and involve the capacity to change body position quickly and accurately (Brown, 2001). According to Kollmitzer et al. (2000), strength and balance are important components for postural control. Together then, the motor skills clustering together here require strength, upright position and balance to maintain posture during the dynamic movements needed to accomplish the tasks (Burton & Davis, 1992; Kollmitzer et al., 2000; Westcott et al., 1997). Therefore, controlling body posture is an important component in this factor. Two main functions of posture are ‘to remain inside the supporting surface’ and ‘as a reference frame for perception and action with respect to the external world’ (Massion, 1994, p. 877). Since these tasks require control and adaptable force to regulate the posture, this factor was labelled ‘postural control’ (Burton & Davis, 1992; Kent, 1994). Factor Three explained 8.41% of variance and had high loadings on one-foot balance with eyes open and one-foot balance with eyes closed. Both motor skills require individuals to maintain or control their centres of mass relative to their base of support to prevent falling and complete desired movements’ (Westcott et al., 1997). Additionally, being able to balance on one leg requires an ability to focus attention while inhibiting extraneous motor movements. Success in these two motor skills requires control of extraneous motor movements and one’s centre of mass, especially when the eyes are closed. Fleishman (1964) suggested that skills measured in situations with eyes open or closed assesses gross body equilibrium. Since the more important items loaded on this factor reflected an ability to maintain vertical balance in a static position (Bass, 1939; Burton & Davis, 1992), this factor was named ‘static balance’. 89 Despite the basketball throw and vertical jump motor skills failing to meet the cut-off value of .50 required for inclusion in a factor, they did load minimally in a direction consistent with those factors. Both loaded above .31 on postural control. The basketball throw and vertical jump require strength, upright position and balance to maintain posture whilst performing (Burton & Davis, 1992; Kollmitzer et al., 2000; Westcott et al., 1997). These characteristics are fundamental to the other motor skills making up postural control. Also, the basketball throw exhibited a low loading of .33 for static balance. As with the postural control required for the one-foot balance, the basketball throw also requires balance ability. The fact that the loading is negative, is probably due to the nature of the basketball throw which is performed explosively in complete contrast to the very static nature of the one-foot balance skills. Higher-Order Factor Analysis. The higher-order factor analysis conducted on the three identified factors from the combined AIS+BMC (i.e., movement coordination, postural control and static balance) revealed one element. This higher-order element accounted for 55.92% of the variance, and the loadings for the first-order factors ranged from .60 to .82. Given that one element encompassed all of the first-order factors it is suggested that this demonstrates the presence of ‘g’ in motor skill ability, or general motor ability. This hierarchical pattern of factors is similar to that found in factor analysis research examining the existence of general intelligence. For instance, Johnson et al. (2004) demonstrated the existence of a ‘g’ in general intelligence via a second-order confirmatory factor analytic approach of three cognitive test batteries. The three test batteries were the Comprehensive Ability Battery (CAB: Hakstian & Cattell, 1975), the Hawaii Battery, including Raven’s Progressive Matrices (HBRAVEN: Defries et al., 1974; Kuse, 1977), and the Weschler Adult Intelligence Scale (WAIS: Weschler, 1955). What emerged from this analysis were 13 first-order factors. The first-order factor loadings on the secondorder ‘g’ factor for the CAB test ranged from .50 to .98. For the HBRAVEN test, these ranged from .46 to .88 and, for the WAIS test, the first-order factor loadings on the second-order ‘g’ factor ranged from .78 to .88. The correlations between these three ‘g’ factors ranged from .99 to 1.00, thereby indicating that the concept of ‘g’ as a unitary construct was evident (Johnson et al., 2004). Johnson et al. (2008) set out to replicate this finding in another sample by examining five cognitive test batteries. Again, a second-order confirmatory factor analytic approach of the test batteries was undertaken. Initially, exploratory factor analyses were performed on each of the batteries in order to develop second-order factor models independently. The batteries were the Test Battery of the Royal Dutch Navy (see Buros, 1959), the Factored Aptitude Test (see Buros, 1953), the Cattel Culture Fair Test (see Buros, 1959), the General Aptitude Test Battery (van der Giessen, 1960) and the Groninger Intelligence Test (Snijders & Verhage, 1962). The first-order factor loadings on the second-order ‘g’ 90 factor for the Test Battery of the Royal Dutch Navy test, ranged from .61 to .92; and for the Factored Aptitude Test these ranged from .46 to 1.00. The Cattel Culture Fair Test reported first-order factor loadings on the second-order ‘g’ factor ranging from .50 to .73; for the General Aptitude Test Battery, first-order factor loadings on the second-order ‘g’ factor ranged from .25 to .81; and the first-order factor loadings on the second-order ‘g’ factor for the Groniger Intelligence Test ranged from .34 to .90. Finally, the correlations between the five ‘g’ factors ranged from .77 to 1.00, thereby indicating that the concept of ‘g’ as a unitary construct was evident. The AIS+BMC motor skills, first-order factors and higher-order element for all participants is illustrated in Figure 4. Figure 4. The AIS+BMC motor skills, first-order factors and higher-order element. 91 APPENDIX J 6.4. RESULTS: GROUPS DERIVED FROM MAND SCORES – FEMALE ADOLESCENTS Originally, the study aimed to perform discriminant analysis separately on the boys and the girls. However, owing to the Poor coordination group of the boys failing to meet the recommended minimum 20 cases per group (Hair et al., 1998), only the adolescent girls were analysed. The results of the stepwise discriminant analysis revealed that three motor skills entered into the discriminant function. Discrimination increased with the addition of each motor skill and by the third step could discriminate between the motor coordination groups. Specifically, the Balance Eyes Closed entered on the first step Wilks Lambda = .82, F(2, 158) = 17.10, p < .001, the Balance Eyes Open test on the second step Wilks Lambda = .75, F(4,314) = 12.32, p < .001, the Shuttle Run With Object test on the third step Wilks Lambda = .70, F(6,312) = 10.06, p < .001. Two canonical discriminant functions were computed for the AIS+BMC (see Table 36). Both functions were significant and indicated a strong association between the groups and predictors for each function. Specifically, the first function produced a Wilks Lambda = .70, with a Chi-square (6) = 55.52, p < .001, and the second function produced a Wilks Lambda = .96, with a Chi-square (2) = 6.85, p < .034. The canonical R2s for the two functions were .27 for the first function and .04 for the second function. The two discriminant functions accounted for about 89% and about 11%, respectively, of the between-group variability. An examination of the unstandardised canonical discriminant functions evaluated at group means reveals that the first function maximally separates the High coordination group from the Poor group, with the Normal group in between. The second function discriminates the Normal group from the Poor and High groups. An examination of the structure correlations for the discriminant analysis did not reveal additional motor skills that had a substantial effect on discriminating between the three coordination groups beyond that indicated by the stepwise estimation. Thus, the first discriminant function that the structure correlations indicated was that the motor skills Balance Eyes Closed, Balance Eyes Open, and Shuttle Run with Object were able to discriminate between the High coordination group from both the Normal and Poor coordination groups. The coordination groups’ performances on these motor skills revealed that the High coordination group recorded better performances than either the Normal or the Poor coordination groups - Balance Eyes Closed (Mean = 86.54, SD = 27.08 vs Mean = 56.08, SD = 33.93 and Mean = 37.45, SD = 29.47, respectively), the Balance Eyes Open (Mean = 119.75, SD = 1.22 vs Mean = 112.54, SD = 15.40 and Mean = 100.73, SD = 20.68, respectively), and the Shuttle Run With Object test (Mean = 10.58, SD = 92 .93 vs Mean = 11.64, SD = 1.38 and Mean = 11.74, SD = 1.26, respectively). The discriminatory power of these tests was relatively good, given their respective potency indices. For the second discriminant function, the motor skills found to discriminate the Normal coordinated group from the Poor and High coordinated counterparts appears to be the Balance Eyes Open (Mean = 112.54, SD = 15.40 vs Mean = 100.73, SD = 20.68 and Mean = 119.75, SD = 1.22, respectively), and the Shuttle Run With Object (Mean = 11.64, SD = 1.38 vs Mean = 11.74, SD = 1.26 and Mean = 10.58, SD = .93, respectively). 93 Table 8. Standardised Weights, Structure Canonical Coefficient Values, Potency Index, Canonical Correlations, Eigenvalues and Group Centroids for the Three Female Motor Coordination Groups. Discriminant Function First Second SW Value PI SW Value PI Balance Eyes Closed .58 .77 .53 .28 .17 .00 Shuttle Run NI .46 .19 NI .45 .02 Hopping Speed NI .40 .14 NI .21 .00 Zigzag Run NI .33 .10 NI .28 .01 Multistage Fitness Test NI .33 .09 NI .21 .00 40m Sprint NI .32 .09 NI .27 .01 Quadrant Jump NI .24 .05 NI .09 .00 Hopping-in-Square NI .17 .02 NI .04 .00 Dynamic Balance NI .16 .02 NI .14 .00 Basketball Throw NI .12 .01 NI .03 .00 Balance Eyes Open .51 .67 .40 -.79 -.70 .05 Shuttle Run With Object .41 .51 .23 .63 .64 .04 Vertical Jump NI .08 .01 NI .24 .01 Canonical Correlation .52 .21 Eigenvalue .36 .05 Group Centroids Poor -1.08 .37 Normal -.03 -.13 High 1.15 .30 Note. SW: Standardised weights. NI: Not included in the stepwise solution. Value: Structure correlations with correlations greater than .50 in bold. PI: Potency Index. For both motor skills, the performance of the Normal motor coordination group was better than that of the Poor coordination and less than that for the High motor coordination group. However, the discriminatory power of these tests is relatively low according to their relative potency indices of .05 and .04, respectively. 94 The jackknife classification analysis revealed that 115 (71.4%) of the participants were classified correctly, compared with 89 (55.09%) who would be correctly classified by chance alone. However, using sample proportions as prior probabilities, it appears that only the Normal coordination group was more likely to be correctly classified (91.3%). Specifically, 105 Normal individuals were classified correctly, five Normal individuals were classified as Poor (4.3%) and five Normals were classified as High (4.3%). The High coordination group reported 16.7% correct classifications (n = 4), with the rest misclassified as Normal (83.3%). The Poor coordination group had six individuals correctly classified (27.3%). However, the other sixteen Poor individuals were classified as Normal (72.7%). Thus, the classification rate of around 71% was achieved despite a disproportionate number of cases being classified as Normal. Finally, an examination of the misclassified adolescent girls revealed the following (see Table 37). All 16 misclassified Poor motor coordination individuals were misclassified as Normal. With the exception of the Shuttle Run with Object, the 40m Sprint test and the Vertical Jump, the misclassified girls performed the motor skills to a higher standard over their correctly classified Poor cohorts, with a significant performance improvement for the Balance Eyes Open (p < .001). The five Normal motor coordination individuals who were misclassified as High were able to perform all of the motor skills to a higher standard over their correctly classified Normal cohorts. Significant performance improvements were found for the Balance Eyes Closed, Balance Eyes Open and the Shuttle Run With Object motor skills (p < .001). The five Normal motor coordination individuals who were misclassified as Poor, with the exception of Shuttle Run with Object and Vertical Jump, performed all of the motor skills to a lower standard over their correctly classified Normal cohorts, with a significant performance decrement for the Balance Eyes Open test (p < .003). All of the misclassified High motor coordination female adolescents were misclassified as Normal. For these individuals, with the exception of Dynamic Balance, Basketball Throw and Hopping-in-Square, these individuals performed the motor skills to a lower standard than their correctly classified High cohorts. 95 Table 9. Profiling Correctly Classified & Misclassified Observations in the Three-Group Discriminant Analysis for Female Adolescents. Mean Scores Motor Group/ Correctly Motor Skills Classified Misclassified N Poor (n = 6) t test Difference t-value Sig. H (n = 16) (n = 0) N H N H N H Balance Eyes Closed a 22.67 43.00 - -20.33 - -2.83 - .029 - Shuttle Run 11.51 11.21 - .30 - .54 - .598 - Hopping Speed 13.79 10.74 - 3.06 - 2.03 - .056 - Zigzag Run 13.84 13.45 - .39 - .53 - .602 - Multistage Fitness Test 9.50 12.19 - -.269 - -1.41 - .174 - 40m Sprint 8.94 8.97 - -.03 - -.06 - .950 - Quadrant Jump 24.25 28.44 - -4.19 - -1.11 - .281 - Hopping-in-Square 40.12 49.75 - -9.63 - -2.99 - .007 - Dynamic Balance 14.67 18.31 - -3.64 - -1.62 - .121 - Basketball Throw 3.80 4.34 - -.54 - -1.83 - .082 - Balance Eyes Open a 72.33 111.38 - -39.05 - -7.56 - .000 - Shuttle Run With Objecta 11.60 11.80 - -.20 - -.33 - .748 - Vertical Jump 22.67 22.44 - .23 - .08 - .935 - P H (n = 105) (n = 5) (n = 5) P H Balance Eyes Closed a 54.35 30.00 118.40 Shuttle Run 10.99 11.01 9.92 -.02 1.07 -.05 Hopping Speed 10.45 11.96 8.18 -1.51 2.27 -1.19 1.88 .237 .063 Zigzag Run 13.24 13.85 11.57 -.61 1.67 -.94 6.60 .350 .001 Multistage Fitness Test 11.84 11.80 20.00 .04 -8.16 .43 2.11 .667 .101 40m Sprint 8.86 9.23 7.44 -.37 1.42 ` -.62 2.41 .538 .018 Quadrant Jump 29.37 25.10 33.80 4.27 -4.43 Normal - t-value P H 24.35 -64.05 P H 3.35 -19.42 .015 .001 2.10 .962 .038 1.30 -1.35 .198 .179 96 Table 37 continued. Motor Group/ Correctly Motor Skills Classified Misclassified Difference P H P H t-value P H Sig. P H Hopping-in-Square 45.86 41.00 56.80 4.86 -10.94 1.20 -2.63 .232 .010 Dynamic Balance 19.83 18.40 26.20 1.43 -6.37 .63 -2.82 .529 .006 Basketball Throw 4.20 4.02 4.86 .18 -.660 .51 -1.87 .609 .604 Balance Eyes Open a 114.73 59.00 120.00 55.73 -5.27 6.82 -5.34 .002 .001 Shuttle Run With Objecta 11.70 11.65 10.30 .05 1.40 .07 Vertical Jump 23.20 26.40 27.20 -3.20 -4.00 P N P N P N P N High (n = 5) Balance Eyes Closed a (n = 0) (n = 19) 8.50 .943 .001 -1.14 -1.49 .258 .139 113.00 - 79.58 - 33.42 - 2.48 - .011 Shuttle Run 9.63 - 10.33 - -.70 - -1.74 - .095 Hopping Speed 7.74 - 8.61 - -.87 - -1.17 - .255 Zigzag Run 11.85 - 12.36 - -.51 - -1.19 - .248 Multistage Fitness Test 15.60 - 13.89 - 1.71 - .66 - .515 40m Sprint 7.83 - 8.01 - -.18 - -.40 - .690 Quadrant Jump 37.00 - 33.82 - -3.18 - .83 - .417 Hopping-in-Square 48.40 - 48.79 - -.39 - -.13 - .900 Dynamic Balance 18.40 - 20.74 - -2.34 - -1.01 - .323 Basketball Throw 4.38 - 4.68 - -.30 - -.88 - .390 120.00 - 119.68 - .32 - .50 - .619 Shuttle Run With Objecta 9.94 - 10.75 - -.81 - -1.83 - .081 Vertical Jump 26.20 - 23.89 - 2.31 - 1.42 - .175 Balance Eyes Open a Note. a =Variables included in the stepwise estimation. P = Poor, N = Normal, H = High. NA = Not available. A Bonferroni correction was used to adjust the .05 significance value to .0038. Significant differences are in bold. 97 6.5. DISCUSSION – FEMALE ADOLESCENTS The results of the stepwise estimation revealed three motor skills that could maximally separate the three motor coordination groups: Balance Eyes Closed, Balance Eyes Open and Shuttle Run with Object. Although this is the best set of motor skills reported, the discriminant functions were examined to see where discrimination would occur if all 13 motor skills were included in the model. An examination of the discriminant functions did not reveal additional motor skills that had a substantial effect on discriminating between the three motor coordination groups beyond that indicated by the stepwise estimation. Two discriminant functions were derived from the analysis and, given the magnitude of the canonical structure coefficients, the potency indices and the canonical correlations for these functions, the first function was deemed important. The first function indicated the motor skills that can maximally separate the High coordination group from the Poor group with the Normal group in between. Thus, when one considers all of the motor skills as a package, the Balance Eyes Closed, Balance Eyes Open and Shuttle Run with Object were found to be the best set to separate the High motor coordination group from the other two coordination groups. An examination of the mean performances of the three coordination groups on these four motor skills indicated that the High motor coordination group consistently outperformed the other coordination groups. The second discriminant function indicated that the best motor skills for discriminating the Normal coordination group from the other two coordination groups were Balance Eyes Open and Shuttle Run with Object. An examination of the performance means for these motor skills revealed that the Normal group recorded better performances than the Poor coordination group, and lower performances than the High coordination group. However, according to their respective potency indices, the discriminatory power of these two motor skills was relatively low. When assessing the fit of the discriminant model, the predictive accuracy level of the discriminant functions was examined. Using jackknife classification, the functions could reasonably classify the adolescents. Specifically, the hit ratio was 89%, which is considerably higher than the 56% who would be correctly classified by chance alone. The Normal group had the best correct classification hit ratio with 91% of Normals being classified correctly, 4.5% classified as Poor and 4.5% classified as High. The High group only had a correct classification hit ratio of 17%, with 83% being classified as Normal. Finally, the Poor coordination group only had a correct hit ratio of 27%. The remaining Poor motor coordination individuals were misclassified as Normal (73%). Once again, what is note worthy in these findings is the disproportionate number of cases being classified as Normal. For instance, most of the High coordination group, and over two-thirds of the Poor coordination group were misclassified as Normal. Therefore, several female adolescents who performed the MAND 98 motor skills quite poorly, and were categorised as Poor in basic motor coordination, were able to perform the AIS+BMC motor skills at a level higher than their correctly classified cohorts. Conversely, there were female adolescents who performed the MAND motor skills very well and were categorised as High in basic motor coordination, but 83% of these individuals performed the AIS+BMC skills at a level lower than their correctly classified cohorts. A: An examination of the misclassifications supports such a view. For example, those Poor motor coordination individuals who were misclassified as Normal, except for Shuttle Run with Object, the 40m Sprint and the Vertical Jump, as a group, performed the motor skills to a higher standard over their correctly classified Poor cohorts. In addition, they performed the Balance Eyes Open motor skill for significantly longer than the correctly classified Poor cohorts. The Normal motor coordination individuals who were misclassified as High performed all of the motor skills to a higher standard over their correctly classified Normal cohorts, with significant performance improvements for the Balance Eyes Closed, Balance Eyes Open and the Shuttle Run with Object motor skills. The Normal motor coordination individuals who were misclassified as Poor, with the exception of Shuttle Run with Object and Vertical Jump, performed all of the motor skills at a lower standard than their correctly classified Normal cohorts, with a significant performance decrement for the Balance Eyes Open. Finally, the High motor coordination individuals who were misclassified as Normal, with the exception of the Dynamic Balance, Basketball Throw and Hopping-in-Square, performed the motor skills to a lower standard over their correctly classified High cohorts. Thus, it appears that the misclassifications found here once again make sense in terms of performance. Those individuals misclassified to a level higher, generally performed the AIS+BMC motor skills to a higher level than their correctly classified cohorts; and those individuals misclassified to a level lower, generally performed the AIS+BMC motor skills to a lower level than their correctly classified cohorts. Again, these findings are an important reminder about individual differences in motor skill performance and that performance in one set of motor skills does not necessarily translate to similar levels of performance in a different set of motor skills. It is clear that a large number of female adolescents performed the MAND motor skills to either a very low standard or a very high standard, and this level of performance was not translated across to their AIS+BMC performances. The particular reasons as to why there were such large misclassifications for the Poor and High coordination groups remain unclear and awaits future investigation. 6.9. RESULTS: GROUPS DERIVED FROM ‘g’ SCORES - FEMALE ADOLESCENTS Originally, discriminant analyses were to be performed separately on the boys and the girls. However, owing to both the Poor and High ability groups of boys failing to meet the recommended minimum 20 cases per group (Hair et al., 1998), only the adolescent girls were analysed. A total of 161 female 99 participants were used in the following analyses (21 Poor motor ability, 120 Normal motor ability and 20 High motor ability). The results of the stepwise discriminant analysis revealed seven motor skills that could maximally separate the three motor ability groups. Discrimination increased with the addition of each test and by the seventh step achieved the ability to discriminate between the motor ability groups. Specifically, Hopping Speed entered on the first step Wilks Lambda = .58, F(2, 158) = 56.72, p < .001, Quadrant Jump on the second step Wilks Lambda = .46, F(4,314) = 36.91, p < .001, Balance Eyes Open on the third step Wilks Lambda = .40, F(6,312) = 30.54, p < .001, Dynamic Balance on the fourth step Wilks Lambda = .35, F(8,310) = 27.26, p < .001, Balance Eyes Closed on the fifth step Wilks Lambda = .31, F(10,308) = 24.53, p < .001, Hopping-in-Square on the sixth step Wilks Lambda = .29, F(12,306) = 22.03, p < .001, and the Multistage Fitness test on the seventh step Wilks Lambda = .27, F(14,304) = 20.04, p < .001. Two canonical discriminant functions were found for the AIS+BMC (see Table 41). Both functions were significant, and indicated strong associations between the groups and predictors for each function. Specifically, the first function produced a Wilks Lambda = .27, with a Chi-square (14) = 202.66, p < .001, and the second function produced a Wilks Lambda = .87, with a Chi-square (6) = 21.78, p < .002. The canonical R2s for the two functions were .83 for the first function and .36 for the second function. The two discriminant functions accounted for about 94% and about 6%, respectively, of the between group variability. An examination of the unstandardised canonical discriminant functions evaluated at group means reveals that the first function maximally separates the Poor motor ability group from the High group, with the Normal group in between. The second function discriminates the Normal motor ability group from the High and Poor groups. 100 Table 10. Standardised Weights, Structure Canonical Coefficient Values, Potency Index, Canonical Correlations, Eigenvalues and Group Centroids for the Three Female Motor Ability Groups. Discriminant Function First Second SW Value PI SW Value PI Hopping Speed .39 .56 .29 -.69 -.38 .01 Quadrant Jump .37 .49 .22 .34 .19 .00 Dynamic Balance .41 .46 .19 -.06 .06 .00 Multistage Fitness Test .19 .38 .13 .60 .38 .01 Balance Eyes Closed .35 .37 .13 .34 .17 .00 Zigzag Run NI .36 .12 NI -.02 .00 Shuttle Run NI .34 .11 NI -.03 .00 40m Sprint NI .27 .07 NI .01 .00 Shuttle Run With Object NI .23 .05 NI -.04 .00 Basketball Throw NI .12 .01 NI .06 .00 Balance Eyes Open .37 .33 .10 -.53 -.49 .02 Hopping-in-Square .26 .33 .10 .39 .39 .01 Vertical Jump NI .01 .00 NI .09 .00 Canonical Correlation Eigenvalue .83 .36 2.21 .15 Group Centroids Low -3.03 .60 Normal .06 -.22 High 2.80 .72 Note. SW: Standardised weights. NI: Not included in the stepwise solution. Value: Structure correlations with correlations greater than .50 in bold. PI: Potency Index. 101 An examination of the structure correlations for the discriminant analysis did not reveal additional motor skills that had a substantial effect on discriminating between the three motor ability groups beyond that indicated by the stepwise estimation. Thus, the structure correlations for the first discriminant function suggests that the best test for discriminating between the Poor motor ability group, from both the High and Normal motor ability groups was the Hopping Speed test; with the Quadrant Jump test approaching the cut-off value of .50. The Poor motor ability group recorded lower performances than the Normal or High motor ability groups: Hopping Speed (Mean = 14.58, SD = 3.03 vs Mean = 10.02, SD = 2.06 and Mean = 7.48, SD = .83, respectively) and Quadrant Jump (Mean = 21.52, SD = 4.46 vs Mean = 29.74, SD = 6.44 and Mean = 39.25, SD = 5.96, respectively). The discriminatory power of the Hopping Speed motor skill appears to be relatively good, given its respective potency index. For the second discriminant function, none of the tests exceeded the cut-off value of .50. However, the Balance Eyes Open test approached the cut-off value for discriminating the Normal motor ability group from the High and Poor groups (Mean = 113.78, SD = 12.97 vs Mean = 120.00, SD = .00 and Mean = 94.19, SD = 24.49, respectively). The jackknife classification analysis revealed that 143 (88.8%) of the participants were classified correctly, compared with 94 (58.76%) who would be correctly classified by chance alone. However, using sample proportions as prior probabilities, it appears that only the Normal motor ability group was more likely to be correctly classified (93.3%). Specifically, 112 Normal individuals were classified correctly, five Normal individuals were classified as Low (4.2%) and three Normals were classified as High (2.5%). The High motor ability group reported 75% correct classifications (n = 15), with the other five misclassified as Normal (25%). The Poor motor ability group had 16 individuals correctly classified (76.2%). However, the other five Poor individuals were classified as Normal (23.8%). Thus, the classification rate of around 89% was achieved despite a disproportionate number of cases being classified as Normal. Finally, an examination of female adolescents revealed that the five misclassified Poor motor ability adolescents were misclassified as Normal (see Table 42). With the exception of the Dynamic Balance, Multistage Fitness Test, Zigzag Run, 40m Sprint, Basketball Throw and Hopping-in Square, the misclassified adolescents performed the motor skills to a higher standard than their correctly classified Poor cohorts, with a significant performance improvement for the Balance Eyes Open (p < .001). The two Normal motor ability individuals who were misclassified as High were able, with the exception of Shuttle Run with Object and Vertical Jump, to perform all of the motor skills to a higher standard than their correctly classified Normal cohorts, with significant performance improvements for the Hopping-in-Square motor skill (p < .001). 102 Table 11. Profiling Correctly Classified and Misclassified Observations in the Three-Group Discriminant Analysis for the Adolescent Females. Mean Scores Motor Group/ Correctly Motor Skills Classified t test Misclassified Difference t-value Sig. N H (n = 16) (n = 5) (n = 0) N H N H N H Hopping Speed a 15.38 12.02 - 3.37 - 2.42 - .026 - Quadrant Jump a 20.41 25.10 - -4.69 - -2.26 - .036 - Dynamic Balance a 14.13 12.20 - 1.93 - .95 - .354 - Multistage Fitness Test a 8.88 7.60 - 1.28 - 1.10 - .284 - Balance Eyes Closed a 25.06 34.60 - -9.54 - -.89 - .416 - Zigzag Run 14.76 14.89 - -.13 - -.21 - .833 - Shuttle Run 12.25 11.97 - .28 - .51 - .614 - 40m Sprint 9.53 9.74 - -.21 - -.35 - .730 - Shuttle Run With Object 12.65 12.40 - .26 - .34 - .741 - Basketball Throw 3.78 3.73 - .04 - .11 - .91 - Balance Eyes Open a 86.94 117.40 - -30.46 - -4.73 - .000 - Hopping-in-Square a 41.13 38.20 - 2.93 - .76 - .454 - Vertical Jump 18.50 20.60 - -2.10 - -.98 - .341 - P H (n = 115) (n = 3) (n = 2) P H P H Hopping Speed a 9.95 14.27 7.85 -4.32 2.11 -3.80 1.52 .000 .132 Quadrant Jump a 29.73 26.00 36.25 3.73 -6.52 5.56 -1.42 .000 .160 Dynamic Balance a 19.83 17.33 28.00 2.49 -8.17 1.06 -2.87 .293 .005 Multistage Fitness Test a 12.20 8.67 13.00 3.53 -.80 1.53 Poor Normal - t-value P H -.28 .128 .778 Table 42 continued. Motor Group/ Correctly Motor Skills Classified Misclassified Difference t-value Sig. 103 P H P H P H P H Balance Eyes Closed a 57.41 40.00 93.50 17.41 -36.09 Zigzag Run 13.01 14.78 12.57 -1.77 .45 -2.46 .51 .015 .611 Shuttle Run 10.81 11.95 10.43 -1.14 .38 -2.07 .57 .040 .569 40m Sprint 8.79 8.97 7.99 -.18 .81 -.25 .91 .801 .365 Shuttle Run With Object 11.48 11.97 12.12 -.49 -.64 -.68 -.72 .498 .470 Basketball Throw 4.24 4.83 5.00 -.60 -.76 -1.46 -1.55 .148 .125 Balance Eyes Open a 113.62 116.00 120.00 -2.38 -6.38 -.31 Hopping-in-Square a 46.17 39.67 57.00 6.51 -10.83 1.50 -2.05 .136 .042 Vertical Jump 23.74 22.67 22.00 1.07 1.74 .32 .42 P N (n = 15) (n = 0) (n = 5) P N P N P N Hopping Speed a 7.73 - 6.76 - .97 - 2.59 - .019 Quadrant Jump a 40.80 - 34.60 - 6.20 - 2.21 - .040 Dynamic Balance a 25.20 - 23.80 - 1.40 - .57 - .577 Multistage Fitness Test a 18.67 - 15.40 - 3.27 - 1.01 - .327 Balance Eyes Closed a 100.80 - 71.00 - 29.80 - 2.29 - .034 Zigzag Run 11.70 - 11.42 - .28 - .81 - .430 Shuttle Run 9.95 - 9.12 - .83 - 3.14 - .006 40m Sprint 7.43 - 7.05 - .38 - 1.31 - .207 Shuttle Run With Object 10.57 - 9.45 - 1.12 - 2.54 - 0.02 Basketball Throw 4.89 - 4.84 - .05 - .13 - .901 Balance Eyes Open a 120.00 - 120.00 - .00 - NA - NA Hopping-in-Square a 56.80 - 53.20 - 3.60 - .71 - .488 Vertical Jump 27.60 - 25.80 - 1.80 - .68 - .506 High .90 -4.45 .372 .089 -.68 .756 .497 .753 .677 Note. a = Variables included in the stepwise estimation. P = Poor, N = Normal, H = High. NA = Not available. A Bonferroni correction was used to adjust the .05 significance value to .0038. Significant differences are in bold. 104 The three Normal motor ability individuals misclassified as Low, with the exception of the Basketball Throw and Balance Eyes Open, performed all of the motor skills to a lower standard than their correctly classified Normal cohorts. Significant decrements were found for Hopping Speed and Quadrant Jump (p < .001). Five misclassified High motor ability adolescents were misclassified as Normal. With the exception of Hopping Speed, Zigzag Run, 40m Sprint and Shuttle Run with Object, they performed the motor skills to a lower standard than their correctly classified High cohorts. 6.10. DISCUSSION – FEMALE ADOLESCENTS The results of the stepwise estimation revealed seven motor skills that could maximally separate the three motor ability groups - Hopping Speed, Quadrant Jump, Balance Eyes Open, Dynamic Balance, Balance Eyes Closed, Hopping-in-Square and the Multistage Fitness test. Although this is the best set of motor skills reported, the discriminant functions were also examined to see where discrimination would occur if all 13 motor skills were included in the model. An examination of the discriminant functions did not reveal additional motor skills that had a substantial effect on discriminating between the three motor ability groups beyond that indicated by the stepwise estimation. Two discriminant functions were derived from the analysis and, given the magnitude of the canonical structure coefficients, the potency indices and the canonical correlations for both functions, the first function was deemed slightly more important than the second function. The first function indicated the motor skills that can maximally separate the Poor motor ability group from the High group, with the Normal group in between. When one considers all of the motor skills as a package, only Hopping Speed was found to discriminate the Poor motor ability group from both the Normal and High ability groups. An examination of the mean performances of the three motor ability groups on this motor skill indicated that the Poor ability group performed this skill at a considerably lower level than either of the other two ability groups. None of the motor skills in the second function were sufficiently strong enough to clearly discriminate the Normal ability group from both the High and Poor ability groups. However, Balance Eyes Open did approach the .50 cut-off. The performance mean for this motor skill revealed that the Normal group recorded better performances than the Poor ability group and lesser performances than the High motor ability group. However, according to its potency index, the discriminatory power of Balance Eyes Open was low. When assessing the fit of the discriminant model, the predictive accuracy level of the discriminant functions was examined. Using jackknife classification, the functions classifed the female adolescents quite well. Specifically, the hit ratio was 89%, which is considerably higher than the 59% who would be correctly classified by chance alone. The Normal ability group had the best correct classification hit ratio, with 93% of Normals being classified correctly, 3% misclassified as Poor and 4% 105 misclassified as High. The High motor ability group had a correct classification hit ratio of 75%, with 25% being misclassified as Normal. Finally, the Poor motor ability group had a correct hit ratio of 76% and the remaining Poor motor ability individuals were misclassified as Normal (24%). Once again, a disproportionate number of cases were being classified as Normal, but the percentages were not as high as those found for the MAND framework. Using GMA scores to create the ability groups, only 25% of the High motor ability group and 24% of the Low motor ability group were misclassified as Normal. Thus, some female adolescents who were classified as having Poor motor ability when based on their ‘g’ scores, performed some AIS+BMC motor skills at a level higher than those correctly classified. Conversely, female adolescents classified with High motor ability from their ‘g’ scores, performed the AIS+BMC motor skills to a lower level than their correctly classified cohorts. The misclassification results support such a view with Poor motor ability individuals who were misclassified as Normal, with the exception of Dynamic Balance, Multistage Fitness Test, Zigzag Run, 40m Sprint, Basketball Throw and Hopping-in Square, performed the motor skills better than their correctly classified Poor cohorts. In addition, they performed the Balance Eyes Open motor skill for a significantly longer time than their correctly classified Poor ability cohorts. The Normal motor ability individuals who were misclassified as High were able, with the exception of the Shuttle Run with Object and Vertical Jump, to perform the motor skills at a better standard than the correctly classified Normal cohorts; with significant performance improvements for Hopping-in-Square. The Normal motor ability individuals who were misclassified as Poor, with the exception of the Basketball Throw and Balance Eyes Open, performed all motor skills at a lower standard than their correctly classified Normal cohorts; with significant decrements found for Hopping Speed and Quadrant Jump. Finally, the High motor ability female adolescents who were misclassified as Normal, with the exception of Hopping Speed, Zigzag Run, 40m Sprint and Shuttle Run with Object, performed the motor skills at a lower standard than their correctly classified High cohorts. Thus, it appears that the misclassifications found here again make sense in terms of performance. Those individuals misclassified to a higher level generally performed the AIS+BMC motor skills to a higher level than their correctly classified cohorts, and those individuals misclassified to a level lower generally performed the AIS+BMC motor skills to a lower level than their correctly classified cohorts. However, once again these findings are especially intriguing given that the ‘g’ score was derived from the performance of the motor skills making up the AIS+BMC. The particular reasons as to why there are misclassifications for the Low and High motor ability groups are unclear. It is possible that the best set of motor skills as derived by the discriminant analysis on the face of it are quite good at discriminating between the three ability groups, but fall short with particular individuals. Thus, it is important for practitioners to examine the nature of the misclassifications and indeed examine each misclassified case separately to determine the nature of these individuals.