Exploring People`s resistance to the Active User Paradox including

Transcription

Exploring People’s resistance
to the Active User Paradox
including personality traits
An investigation of the relationship between
people’s resistance to the Active User
Paradox and the role of geekism, need for
cognition and computer anxiety
Bachelorthesis
Wiebke Stöhr
s1340182
June 2015
University of Twente
Department of Behavioral Science
Human Factors & Engineering (HFE)
Examination Committee
Dr. Martin Schmettow
Dr. Matthijs Noordzij
Table of Contents
Abstract………………………………………………………………………………………3
Samenvatting………………………………………………………………………………...4
1. Introduction……………………………………………………………………………...5
2. Method…………………………………………………………......................................9
2.1 Participants…………………………………………………………………………....9
2.2 Apparatus…………………………………………………………………………….10
2.3 Procedure…………………………………………………………………………….11
2.4 Personality measures………………………………………………………………...11
2.5 AUP measures………………………………………………………………………..12
2.6 Research Design……………………………………………………………………..21
2.7 Data analysis…………………………………………………………………………22
3. Results…………………………………………………………………………………...22
3.1 Demographics………………………………………………………………………...22
3.2 Descriptives…………………………………………………………………………..23
3.3 Hypothesis testing…………………………………………………………………....26
4. Discussion…………………………………………………………………………….....28
4.1 Limitations…………………………………………………………………………...34
4.2 Future Research………………………………………………………………………35
4.3 Conclusion……………………………………………………………………………35
References
Appendix
Abstract
The following study aimed at exploring people’s resistance to the Active User Paradox (AUP)
with regard to several personality traits. Hypotheses were formulated relying on the
personality traits geekism, need for cognition and computer anxiety and their association with
the AUP. Therefore, this study tries to unravel the AUP through focusing on personality traits
that could influence people’s resistance to the AUP.
To assess people’s resistance to the AUP, an experiment was carried out that measures
the effort that people invest to solve tasks on an explorative- and challenge seeking level. The
experiment consisted of several tasks that had to be solved using the graphical program GIMP
and the Word processor WORD. To gather data about the personality traits geekism, need for
cognition and computer anxiety of the participants, several questionnaires were used. 28
respondents participated in this study. The data were analyzed using correlation analyses
between people’s resistance to the AUP and the personality traits.
The results imply that there is a moderate to strong association between people’s
resistance to the AUP and a high level of need for cognition. Furthermore, people’s resistance
to the AUP was positively associated with geekism and negatively associated with computer
anxiety. This study can serve as a starting point for further investigations on the AUP and
personality traits.
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Samenvatting
Het doel van deze studie is het verkennen van de relatie tussen het „Active User
Paradox“ (AUP) en verschillende karaktereigenschappen. Daarbij wordt vooral gekeken naar
de mate aan weerstand die mensen kunnen bieden aan het AUP afhankelijk van verschillende
karaktereigenschappen zoals geekism, need for cognition en computer anxiety. Hypothesen
werden ontwikkeld om de relaties tussen deze karaktereigenschappen en het AUP te
onderzoeken.
Om de weerstand van de respondenten tegen het AUP te meten wordt een experiment
uitgevoerd. Daarbij moeten de respondenten verschillende taken aan de computer doorlopen.
Deze moeten worden opgelost met het grafiek programma GIMP of het Woord programma
WORD. Om de weerstand tegen het AUP te meten wordt gekeken hoeveel moeite mensen
besteden aan het oplossen van deze taken met het oog op hun exploratief- en uitdagend gedrag.
Op basis van deze observaties wordt later een som voor het AUP berekent. Deze som wordt
dan op hun relatie tot de karaktereigenschappen geekism, need for cognition en computer
anxiety onderzoekt. De data voor de karaktereigenschappen worden via vragenlijsten
verzameld. Deze moeten de respondenten invullen zodat hun score voor de desbetreffende
schaal kann worden berekend. De data van het AUP en de karaktereigenschappen werden dan
geanalyseerd met correlatie analyses.
De resultaten wijzen erop dat er een sterke positieve associatie bestaat tussen de
weerstand die mensen kunnen bieden aan het AUP en need for cognition. Verder werd er een
positieve associatie gevonden tussen het AUP en geekism en een negatieve associatie tussen
het AUP en computer anxiety. Deze resultaten geven inzicht in hoeverre de karakter van een
mens zijn weerstand tegen het AUP kan bepalen. Dit kann als aanknopingspunt voor verder
onderzoek fungeren.
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1. Introduction
The 21st century is dominated by a growing market of new technologies and innovations.
Technology pioneers of this century like Steve Jobs or Mark Zuckerberg have driven this
progress nearly to its optimum and the research on technology still continues. Researchers are
continuously busy making systems more efficient through upgrading old functions or adding
new functions to a system. These rising changes of technology present people with the
challenge of dealing with always becoming complexer systems (O'Brien, 2007).
Concentrating on the development
of new innovations, progressive technologies and
complexer systems, engineers often forget the users. Are the users really prepared for the
challenges of new complexer technologies?
There are observations of users that are not able to deal with the ever-growing supply
of new systems and functions. Several user studies done at the IBM User Interface institute in
the early 1980s showed that users do not read manuals but start using new software
immediately (Nielsen, 1998). Out of these observations, Carroll and Rosson (1987)
introduced the “paradox of the active user” (AUP). This paradox deals with the fact that users
immediately get active starting to use a new software without making any effort to read its
manual first or go through other learning processes to save time and get their task done
quickly. The paradox that arises out of this fact is that users would save more time in the long
term as they would take some time learning about the software first so that they can optimize
the operation of the new software (Carroll & Rosson, 1987). But is this paradox applying to
all users?
There are indications for individual differences between users in dealing with new and
complex technologies (Schmettow, Noordzij, & Mundt, 2013). What is it for example that
made Steve Wozniak (co-founder of Apple) able to invent a new software system while some
people are not even able to handle this system?
Some people seem to be better at operating complex systems than others and this gives
the impression that those people must have special abilities. From this assumption derives the
concept of “geekism” which states that some people, called geeks, are more computer
enthusiast than others, (Schmettow & Drees, 2014) and therefore appreciate the intellectual
effort to master a technical system (Schmettow et al., 2013). These and other characteristics of
the so-called geeks could explain why some people are capable of dealing with complex
computer systems while others are not. Therefore, it may help to unravel the active user
paradox. But before investigating on the active user paradox and the concept of geekism,
these terms need to be clarified.
5
The active user paradox
The active user paradox was established by Carroll and Rosson (1987) in an age where the
computer was becoming a “powerful and sophisticated information processing technology”
(Carroll & Rosson, 1987) in the everyday life of people. Carroll and Rosson (1987) describe
this period as a paradigm shift in people's way of thinking of computers. As people in earlier
times have still been thinking of computers as helping machines to do things for them, people
nowadays think of computers as machines that will think for us due to technological
development. Therefore, people got increasingly problems with computer use. Carroll and
Rosson (1987) pick up 2 problems and describe them as true paradoxes: (1) people have
considerable trouble learning to use computers and (2) their skills tend to asymptote at
relative mediocrity. These problems arise from conflicting motivational and cognitive
strategies. The production bias is responsible for the motivational paradox and the
assimilation bias for the cognitive paradox. The production bias describes the problem that
people want to produce output which let them focus on their work but at the same time
reduces their motivation to spend time on learning about the system they use to produce
output. Therefore, they use old known procedures, regardless of their inefficacy. On the other
hand, the assimilation bias derives because of the fact that “people apply what they already
know to interpret new situations” (Carroll & Rosson, 1987). Carroll and Rosson (1987)
describe these as “fundamental properties of learning” that arise to new users as well as to
experienced users. Due to the authors, these problems arise because people do not have
enough knowledge to act but do it anyway and strike out into the unknown. They ignore what
is not known to them and interpret what there can be interpreted, no matter how. The active
user paradox appears in a “learning-to-use-a-computer situation” (Carroll & Rosson, 1987)
where users just try out things and try to relate what they already know to what is going on
instead of reading instructions or manuals that would simplify the operation with an unknown
system or function. The authors made suggestions for interface design to overcome the
obstacles of this paradox.
Bhavnani and Bonnie (2000) support these findings in their paper by mentioning that
“several studies […] have shown that despite experience, many users with basic command
knowledge do not progress to an efficient use of applications.”. This shows that even users
with experience can not overcome that obstacle. The authors mention explanations for the
inefficient use of IT based problems under 2 broad categories: (a) efficient strategies not
known and (b) efficient strategies are known but not used. Category a can be compared to the
production bias, mentioned by Carroll and Rosson (1987), which also states that people stick
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to old known strategies by learning a new system or application instead of learning about new
efficient strategies while category b shows similarities to the assimilation bias. However,
Bhavnani & John (2000) conclude that users must learn an intermediate layer of knowledge
that lies between the layers of tasks and tools as task and tool knowledge is not sufficient.
They suggest that “the cost of learning and applying efficient strategies can be easily
addressed by proper strategic instruction.”
Fu & Gray (2004) also addressed the paradox of the active user by mentioning that
“past experiences of procedures influence future choice of procedures”. As the major factors
affecting those future choices, the name “(1) frequency of use, (2) effectiveness (or accuracy),
and (3) efficiency (or speed)” (Fu & Gray, 2004). In a more general manner, they state the
principle of stability as a possible explanation affecting future choices. From their analyses,
the authors conclude that people choose to use suboptimal procedures even when they
apparently had knowledge of better procedures so that they do not follow the normative
principle of rationality but more a principle of past choices that have shown stability in
frequency, effectiveness and efficiency.
Carter et al. (2011) also pick up the frequency of past use as a possible factor that
prevent users from the efficient use of complex applications. The authors link this factor with
the concept of habit that has an inhibitory influence on user's efficiency. They link the factor
computer anxiety to their concept of habit that inhibits user's willingness to innovate with ITbased routines. In contrast, the authors mention the concept of “IT mindfulness” as being a
success factor for the efficient use of IT based routines. This concept is linked to computer
self-efficacy, meaning the belief of one's capability to use the computer (Sam, Othman, &
Nordin, 2005). The authors take the work of Carroll and Rosson (1987) into consideration
while linking the production bias to their concept of “IT mindfulness” and the assimilation
bias to their concept of “habits”. The concept of habits is linked to computer anxiety, which
has been defined as “a fear of computers when using one, or fearing the possibility of using a
computer” (Barbeite & Weiss, 2004) due to affective responses such as “as a reaction of fear
and apprehension, intimidation, hostility, and worries that one will be embarrassed” (Heinssen
et al., 2987). This could be an important factor in people's ability to learn computer skills and
use computers. This assumption is further supported by Sam et al. (2005) who stated that
“lower computer anxiety levels could be important factors in helping people learn computer
skills”. To summarize the findings of Carter et al. (2011), computer anxiety is expected to
have a negative impact on an individual’s propensity to innovate and IT mindfulness is
expected to have a positive impact on this propensity. The authors go even further in
7
suggesting that “individuals who are not predisposed toward novelty seeking or novelty
producing behavior are more susceptible for production bias” (Carter et al., 2011). To be
novelty seeking and novelty producing are characteristics we also found in the concept of
need-for-cognition (Cacioppo & Petty, 1982). As the concept of IT mindfulness shows many
similarities to the concept of need-for-cognition, that will be investigated during this study in
association with the AUP, it is not of great importance for this study. We will concentrate on
the concept of computer anxiety instead that could be worth investigating in association with
geekism as a possible predictor for people’s resistance to the AUP. But first, we should take a
closer look at the concept of geekism.
Geekism
As mentioned earlier by Carter et al. (2011) IT mindfulness is linked to the concept of need
for cognition (Cacioppo & Petty, 1982) as both state an individual's predisposition toward
novelty seeking and novelty producing behavior. With the need for cognition-scale, Cacioppo
and Petty (1982) sought to identify differences among individuals in their tendency to engage
in and enjoy thinking. Their analyses revealed that the need-for-cognition scale can give
information on “people's tendency to enjoy complex problem-solving activities”. Schmettow
(2013) describes geekism with people’s need to explore that leads them to a better
understanding of technology. Furthermore, Schmettow (2013) argued that the “tendency to
enjoy intellectual challenges must be a precondition for geekism.”. This means that only
people scoring high on the need-for cognition-scale, can be called geeks. Therefore, the need
for cognition scale can serve as an instrument to measure geekism. Additionally, Schmettow
(2013) introduces the concept of geekism under the assumption that those people are
computer enthusiast. This trait can be measured by a newly constructed Gex scale and can
also serve as an indicator of geekism. Besides, it would be interesting to investigate to which
extent computer anxiety, as mentioned by Carter et al. (2011) and Sam et al. (2005), is linked
to the concept of geekism.
Next to the mentioned concept of geeks, there is also another by O'Brien (2007) who
speaks of “gifted geeks” in terms of computer technology talent. O'Brien interviewed
technological involved people to get to know what characteristics of giftedness they show and
how these help them operating with technological systems effectively.
An implicit test of Users experience by Schmettow et al. (2013) showed that people
identified as geeks have different associations with Computers than others. They associate
computers with exploration and intellectual mastery (Schmettow & Drees, 2014; Schmettow,
8
Noordzij, & Mundt, 2013) which could lead to the assumption that geeks have a stronger
intrinsic motivation to learn complex IT functions. This could also mean that they have higher
cognitive abilities. White et al. (1997) suggest that cognitive style affects programming
performance and that high cognitive abilities must be available for effective programming.
Regarding these studies, there are reasons to believe that the abilities that characterize
geeks are associated with an effective strategy use of complex computer systems. This could
indicate that there is a relation between geekism and the AUP. It must be investigated if geeks
can overcome the active user paradox due to their special abilities and resources or if they are
also prone to the active user paradox. Additionally, when dealing with geekism, the concept of
Need-for-cognition should be taken into consideration. It seems to be associated with geekism
and the AUP. Furthermore, there seems to be an association between computer anxiety and
geekism that could also influence the AUP. It should be clarified to which extent computeranxiety influences this association. Out of these investigations, the following hypotheses can
be drawn.
1.
A high score on the Geekism Index is positively related to people's resistance to the
AUP.
2.
A high score on the NCS is positively correlated to people's resistance to the AUP.
3.
A High score on the Computer Anxiety Rating scale is correlated to people's
resistance to the AUP.
2. Method
The purpose of the experiment is to explore people's resistance to the AUP with regard to
certain character traits. To assess people's resistance to the AUP, several tasks were invented
with the aim of measuring the effort that people invest to deal with the tasks. To assess
people's resistance to the AUP, it will be analyzed to what extent people show challengingand explorative behavior people during the tasks.
Additionally, the participant's tendency for the character traits geekism, Need-for-cognition
and computer anxiety will be assessed with the help of questionnaires. Later, it will be tested
if there are associations between these character traits and people's resistance to the AUP.
2.1 Participants
For this study, a sample of N=28 participants is chosen. The only necessary condition
participants must fulfill is having at least basic experience with computers and used Microsoft
9
Paint or a comparable graphics program at least once. Persons with color blindness can not
participate. The sample is composed of German participants. To find participants, the
convenience sampling technique will be used. This means that participants are selected
because of their convenient accessibility and proximity to the researcher. As additional
recruiting strategy, the Sona system will be used. It is an online platform where registered
students can choose from a pool of research studies at which study they want to participate.
For their participation they get creditpoints that are a necessary condition for their Bachelor's
degree. Besides, the researcher will search for participants himself through asking friends or
family members for their collaboration.
2.2 Apparatus
For the execution of the experiment, the used computer must be prepared with the necessary
software. Therefore, GIMP, Word and Morae recorder must be installed.
GIMP is a graphical program, comparable to Photoshop, which will be used for the
execution of the tasks. The tasks are composed of several pictures showing different colored
objects like circles, stars and lines. In the instruction form, the participants will be asked to
change the objects, for example to change the color of certain objects, or to erase certain
objects. This is only possible through using the tools of GIMP which means that the
participants have to take a closer look at the graphical program to get used to the functions
and procedures of GIMP.
One further software that is needed for the experiment is the writing processor WORD.
It is needed for further tasks where the participants have to modify certain words of an
available text (e.g. change the colour or letterstyle, underline the words, make them bold).
Therefore, they must use the functions of WORD. These tasks and also the GIMP tasks have
the purpose to challenge the participants and to see how they deal with these challenges on an
explorative- and challenge seeking level. These insights into the participant’s behavior will
later function as a way for assessing the participant’s resistance to the AUP.
The key element of this experiment is the Morae Recorder. It is a video software that it
used to record the participants while they are busy carrying out the tasks. The researcher will
use these videos later for the behavior- and event coding of the participant’s actions. Only
through this qualitative analysis, the researcher can come to a conclusion of the participant’s
resistance to the AUP. Therefore, a scoring guide was constructed. The apparatus will be
described in detail during the further procedure.
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2.3 Procedure
At the beginning of the experiment, the participants will be informed about what they
can expect and then asked to give their informed consent. After they have signed the informed
consent, the experiment can start. Therefore, the participants receive the printed instructions.
At first, they have to carry out three tasks by using the graphical program GIMP.
Therefore, the participants get a tool guide where the function of every available tool is
described shortly. The participants are free to use every available tool to solve the task as
good as possible. However, they must explore how to deal with these tasks through using the
available tools.
After that, they have to do six tasks using the writing software WORD. There are free
to use every function that is offered by WORD but there is no help guide provided as with the
GIMP task. Again, the participants must explore how to deal with these tasks through using
the available functions of WORD by themselves. During the whole experiment, the
participants are allowed to ask technical questions but the researcher will not answer
questions about the tasks.
After the participants have finished the tasks on the computer, the questionnaires will
be given to them by pen and paper and they are asked to fill them in. After finishing the
questionnaires, the experiment ends and the participants will be informed about the purpose of
the experiment by the researcher.
2.4 Measurement of Personality traits
Different questionnaires will be used to test the personality traits of the participants with
regard to their need for cognition, their predisposition for geekism and their level of computer
anxiety.
To test the need for cognition, the need-for-cognition scale of Cacioppo & Petty (1982)
will be used. For testing the predisposition for geekism, the GEX scale, developed by Sander
and Schmettow (2013), will be used and to test the amount of computer-anxiety of a person,
the Computer Anxiety Rating Scale 'CARS' of Heinssen et al. (1987) will be used.
2.4.1 Geekism Index (GEX)
The Gex scale was invented by Sander and Schmettow (2013) to identify people that show
intellectual abilities when it comes to the use and interaction of technological products. These
people could be identified as geeks. With the GEX scale, peoples' tendency for geekism will
be measured. People who score high on the scale, are meant to have a high predisposition for
11
geekism. The questionnaire consists of 15 items that should be answered using a 5 point
Likert-scale. The items cover important aspects of geekism like “understanding of technology”
etc. (Schmettow & Drees, 2014) as it is assumed that geeks have a drive to understand
technical systems, modify and play with them (Schmettow et al., 2013).
The reliability of the scale is α=.96 (Sander and Schmettow, 2013). Sander and Schmettow
(2013) measured the construct validity of the scale through correlational measures with a
scale measuring Material-Possession-Love MPL, a scale measuring the Need for Cognition
and an implicit test measuring geekism. The convergent validity was estimated as acceptable
with a significant correlation between the implicit test and the geekism scale (r=0.53).
2.4.2 Need for cognition scale (NCS)
The need-for-cognition scale was developed by Cacioppo and Petty (1982). As the name
already indicates, it measures to what extent people are willing to explore and learn new
things. The scale consists of 18 items that must be answered with the help of a 7 point-Likert
scale. A high score means a high need for exploration and learning new things while a low
score indicates a low need for learning new things and being explorative. The reliability of the
scale is α=.77 and it appears to be valid as it correlates with relevant constructs (Cacioppo and
Petty, 1982). Additionally, a moderate correlation between NCS and the GEX can be found
(r=.357), indicating that the NCS and the GEX scale measure similar concepts ( Sander and
Schmettow, 2013).
2.4.3 Computer Anxiety Rating Scale (CARS)
The Computer Anxiety Rating Scale (CARS) was found by Heinssen, Glass & Knight (1987)
to measure the amount of computer anxiety that can be seen as a result of people’s “fear and
apprehension, intimidation, hostility, and worries that one will be embarrassed, look stupid, or
even damage the equipment”. Higher scores on the scale indicate higher levels of computer
anxiety. The scale consists of 19 items that have to be rated on a 5 point Likert Scale.
The reliability of the CARS is α=.87 and it was validated by founding correlations with other
relevant constructs like Computer Attitudes scales and fear thermometers (trait, math and text
anxiety) (Heinssen et al., 1987).
2.5 Measurement of people’s resistance to the AUP
The purpose of the experiment is to measure the tendency of individuals to be influenced by
the Acive User Paradox (AUP) when they are confronted with repetitive computer tasks. This
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AUP tendency is ten related to the personality traits of need for cognition, geekism and
computer anxiety. The tendency of the user to fall for the AUP will be assessed on an
explorative and challenging level. In the following paragraph, the tasks of the experiment will
be described.
2.5.1 Tasks
GIMP
The participant has to fulfill three tasks with the graphical program GIMP as described in the
instructions form.
Task 1
In the first task, the participant sees a picture of stars and circles where the stars are red
colored and the circles blue. The participant gets the instruction to remove all objects with a
red color. After finishing that, the participant gets four more of the same pictures but the
colors of the objects have changed. For each picture, the participant has the same task which
is to remove objects with a particular color. He is free to use all the tools he likes.
Figure 1. Gimp Task
Task 2
In the second task, the participant gets a picture with circles and stars again. This time it is his
task to change the color of particular objects, for example to color all blue objects green. After
finishing this task with the first picture, the participants gets four more pictures where the
13
objects remain the same but the colors have changed. The participant has for each picture the
same task which is to change the color of particular objects. He is free to use all the tools he
likes.
Task 3
In the third task, the participant gets a picture of stars and circles again but this time, there are
also lines between the objects in the picture. His task is to remove all lines in the picture
without damaging the objects. After finishing this task for the first picture, the participant gets
four similar pictures where only the color of the objects has changed but he has to carry out
the same task. He is free to use all the tools he likes. An illustration of this task can be found
in the appendix.
WORD
After finishing the tasks with GIMP, the participant has to carry out six more tasks within
Word. Therefore, the participant gets a text of the sun, retrieved from Wikipedia, which is
divided into five paragraphs and where several words are marked blue.
Figure 2. Word Task
Task 1-5
The first task of the participant is to change all marked words in the first paragraph so that
they are underlined, bold, written in the font type “Times New Roman” and red colored.
14
In the following four tasks, the user has to format the marked words of the following parts in
the same way as in the first task except for the fact that the color in which he should change
the words changes for each paragraph.
Task 6
In the sixth and last task, the participant has to change all titles of the text, so that there are
bold, written in the font type Times New Roman, font size 12 and black colored. Additionally,
the participant has to add a numbering for each title (e.g. “1. First paragraph”).
2.5.2 Scoring
The scoring procedure starts with a qualitative analysis of the user's behavior through the
video recording. These results will then be transformed into quantitative scores to make the
AUP measurable. In the following paragraph, the scoring procedure will be described in detail.
Behavior Coding
At first, the video recordings will be evaluated. Having a look at the video recordings, the
researcher can identify in which way the participant has tried to solve the tasks. The
researcher will assess these video observations through behavior- and event coding. Starting
point is a classification system with a certain structure. Here, the methods the participant uses
are noted as well as the time it takes and the parameters used. An example of such a scoring
table can be seen in the following table 1.
Table 1. Example of a Scoring Table
Participant Task
Subtask
Observation Time
Duration
Methods
Parameter
3
2
1
1
00:02:03
00:00:57
RH
DU
3
2
2
2
00:03:00
00:00:40
ER
DU
3
2
3
3
00:03:42
00:00:04
BF
SP
3
2
4
4
00:03:47
00:00:04
BF
SP
…
…
…
…
…
…
…
…
Operator Characteristics
With the help of a coding schema, the methods that the participant has used will be evaluated
on the basis of five characteristics: the specificity, the difficulty, the complexity, the delayed
15
feedback and the parameter demands. Each method that is used will be analyzed on the basis
of these characteristics to calculate the AUP scores later. For each method (operator), it will
be evaluated if the particular characteristic is low, moderate or high. As the scoring of the
operators can be very subjective, all operator characteristics were scored by three raters and
the inter rater reliability was assessed. The final results of the evaluation of these operator
characteristics can be seen in table 2. In the following paragraph, the operator characteristics
will be described shortly.
The specificity of a method is defined by the amount of tasks that can be solved with it
and the amount of different objects that can be manipulated with it. An example of a tool with
a low specificity is the eraser as it can be used for almost all tasks and all objects of the
experiment. More specifically, it can be said that the eraser can be used for all tasks where the
participant must erase certain objects or parts. Additionally, the eraser can be applied to all
objects. In contrast, a tool with a high specificity is the invert selection as the user can only
modify certain objects by using this tool. Besides, this tool can only be used for specific tasks
of the experiment. In summary, it can be said that the specificity of a tool can give an insight
into the user’s mind with regard to the AUP as it shows if the participants choose to use
suboptimal procedures, affected through following a principle of past choices that have shown
stability or if they are more explorative following a principle of rationality that would predict
the use of a more specific tool (Fu & Gray, 2004). Tools with high specificity often lead to
time-saving solutions while it takes more time to solve the tasks when using tools with low
specificity. It is assumed that people, who show a higher resistance to the AUP, tend to choose
a time-saving method.
The difficulty of a method is defined by the expected required experience of the user
with the method or similar operators as well as the expected frequency of use. For example,
the eraser tool of Gimp is defined as a method with a low difficulty as it is easy to use and
most people are familiar to it. Many people recognize the function of the tool when they see
the picture of the eraser or they have already used a similar tool with another graphical
program. Additionally, it is easy to use as the participants just need to press the mouse and
then click on the area they wants to erase. Most tools that are easy to use are not as efficient as
tools that are a bit more difficult to use. Therefore it is assumed that people who choose tools
with a higher difficulty, want to solve the task more efficiently and faster and are therefore
less prone to fall for the AUP. Besides, participants who choose for a more difficult method,
show challenge-seeking behavior which leads to a higher resistance of the AUP. People, who
choose a more difficult tool, invest more time to explore how it works in the beginning but in
16
the end they normally save time as they can solve the task with such a tool faster and more
efficiently. In this way, participants can overcome the production bias as described by Carroll
& Rosson (1987), which increases their resistance to the AUP.
The complexity of a method is defined by the amount of available options or
parameters. For example, the color select tool is defined as a tool with a moderate complexity
as the participant can change some parameters to make that tool working more efficiently. The
more complex a tool is, the more functions of the tool can be changed and the more efficient
the tool can be made. This means that people can solve the task more efficiently if they
choose a tool with a high complexity as they can better adjust the functions of the tool so that
it fits with the tasks. The pencil for example is a tool with a high complexity as people can
adjust several parameters of the tool like the color, size, etc. Therefore, they can make the tool
more precise. However, they have to invest more effort at the beginning with the adjusting of
the parameters than they would have to invest in a simple tool but in the end, the result will be
better. Bhavnani and Bonnie (2000) have shown that despite experience many users with
basic knowledge do not make us of the most efficient applications and they suggest that this
results of not knowing the most efficient strategy or the users know them but do not use them.
Therefore, we suggest that people who explore with complex tools get to know the most
efficient strategy and are assumed to have a higher resistance to the AUP than people who
show less explorative behavior.
The delayed feedback describes that a visual change is not directly visible in the file,
or a preview window after each click. All tools of GIMP are characterized as having a low
delayed feedback as the participant can see the change directly after each click. For example
when he uses the bucket fill tool to change the color of an object, he directly sees the
changing color when he presses with the bucket fill tool on the object so that an object that
was originally green turns into red for example. All tools of GIMP have a low delayed
feedback so that the mental effort necessary to imagine what change would be triggered by
using a certain tool is very low. This is different when using the word processor WORD as
participants first had to adjust certain parameters after they could see the changes. It is
assumed that people who show great levels of mental effort as supposed for geeks
(Schmettow & Passlick, 2013) could imagine a visual change even it is not directly visible in
the file easily. This helps them operating with technological systems (O’Brien, 2007).
Therefore, dealing with delayed feedback seemed to increase people’s resistance to the AUP.
Parameter demands are defined by the necessity to change parameters (good defaults,
change recommended, change required). To solve certain tasks it is required to change the
17
parameters of the tools, for example when the participants have the instruction to change the
color of certain objects. Then, they have to adjust the color of the tool they use. Therefore, the
pencil tool is an operator with moderate parameter demands as people must choose a new
foreground color when using it and also could change the tool size or effects. Contrary to the
pencil, the Cut selection tool has low parameter demands as there are no changes necessary
when using it. People just have to press the del key or select the edit>cut function in the
program to delete an object. No parameter changes are needed. Tools with high Parameter
demands are more difficult to use as they have a higher complexity and can thus be regarded
as tools that support challenge-seeking and explorative behavior. This leads to the supposition
that participants who use these tools and get used to the parameter demands can overcome the
production- and assimilation bias (Carrol & Rosson, 1987) resulting in a higher resistance of
the AUP.
To summarize these operator characteristics in association with the AUP, it can be said
that Persons who are assumed to have a high resistance to the AUP are more likely use and
explore operators (tools) with high specificity, difficulty, complexity, parameter demands and
delayed feedback. This is linked to the supposition that people who are less prone to the AUP
show more willingness to search for methods that might increase their task efficiency and
effectiveness than others, even if this would require additional cognitive effort.
Table 2. Scoring Table Operator Characteristics
Method Operator Description
ID
Specifity Difficulty Complexity Delayed Paramter
feedback demands
CU
Cut
The participant
high
selection presses the del key or
selects edit>cut. This
deletes the currently
selected area.
low
low
low
low
IS
Invert
The participant
high
selection presses select>invert.
This inverts the
currently selected
area.
low
low
low
low
PE
Pencil
low
high
low
medium
The participant
low
optionally selects a
new foreground color
and a tool size, keeps
the mouse button
pressed and moves the
mouse arrow over an
object.
18
PA
Paintbrush The participant
low
new foreground color
and a tool size, keeps
the mouse button
pressed and moves the
mouse arrow over an
object.
low
high
low
medium
ER
Eraser
low
high
low
medium
RS
Rectangle The participant
medium low
select
presses and pulls the
mouse to select in area
in form of a rectangle
high
low
low
ES
Ellipse
select
The participant
medium low
presses
and pulls the mouse to
select an area in form
of
an ellipse.
high
low
low
FS
Fuzzy
Select
The participant
medium medium high
optionally
modifies the threshold
and selects an area
with a
similar color by
clicking
on it.
low
medium
The participant
low
tool size, keeps the
mouse button pressed
and moves the mouse
arrow over an object
Exploratory Behavior
Besides the scoring of operators, exploratory behavior will also be assessed as it is assumed
that a low AUP tendency expresses itself in the willingness to explore the system more deeply.
On the one hand, this can be assessed by the methods and tools the participant users, on the
other hands explorative behavior can be seen in additionally procedures the participant does.
Three operators are categorized as indicating exploratory behavior: Look up function (LF),
Read Handout (RH) and Undo (U).
LF is an operator that shows explorative behavior as it indicates that the participant
invests effort to look up a certain function. This is explorative behavior that can make a
difference in user’s resistance to the AUP.
The operator RH is characterized as an indicator to measure to what extent the
19
participant is willing to invest time to read about the functions of the program. He gets the
opportunity to read the provided handout that describes the different functions of the tool. The
time he invests and the frequency he makes use of this help, are an indicator of his explorative
behavior.
The operator U is defined as explorative behavior as it indicates that the user himself
recognizes that it is better to undo a previously issued function. This self-knowledge is a first
step to self-improvement, meaning that the participant searches for a better way to solve the
task which shows highly explorative behavior.
The scoring and summary of these functions can be looked up in the following table.
Table 3. Scoring table Exploratory behavior
Operator ID
Operator
Description
Parameters
LF
Look up function
user opened help system Duration
to find out
about a specific
function. This is
scored per viewed
function.
RH
Read handout
User reads the provided Duration, function
handout
U
Undo
User undoes a
previously issued
function
Scoring Parameters for Operators
Operators might be used with the default parameters when the parameter demands are not
high, as well as when the parameters were already modified before. As the use of default
parameters needs less cognitive effort, modification of parameters is also coded as noted in
table 4.
Default use (DU) means that the user uses a method without changing parameters.
This suggests that the participant does not invest much effort.
If the participant Sets parameters (SP) for a method, it indicates that he invests more
effort and therefore shows higher cognitive abilities that could protect him from falling for the
AUP.
20
Table 4. Scoring Table Parameters
Parameter ID
Parameter
Description
DU
Default use
User uses a method
without changing
parameters
SP
Set parameters
User sets new parameters
for a method
AUP scores
Relevant variables to calculate these AUP resistance measures are: set parameter amount,
method diversity, read handout duration, undo amount, mean specifity, mean difficulty, mean
complexity, mean delayed feedback and the mean parameter demands. The scoring procedure
for these variables was already described above (see table 2,3 and 4).
Two summary scores will be calculated out of these variables through standardizing
the z-scores of the Challenging- and Explorative behavior and calculating the mean scores. As
a result, we have two variables measuring people's resistance to the AUP:
1.
Exploratory behavior: persons with low propensity for AUP should show stronger
urge to find out the possibilities of the system.
2.
Challenge seeking: persons with a low tendency for AUP should show a stronger will
to master the task in the most appropriate way, which is observed as choice of more
specific, complex and difficult to use functions.
2.5 Research Design
For this study, a mixed method design is chosen that will be carried out under two different
conditions: with manipulation and without manipulation. In the manipulation condition, the
researcher will not tell the participants that they have to perform the same tasks several times.
To guarantee that the participants do not know that they have to carry out several tasks, every
task is written on a new page in the handbook. The participants were told that they have to
turn over a page after they have finished a task. In the other condition, the participants are
aware of the fact that they have to do several tasks. Therefore, all the tasks are written on one
page so that the users can see how many tasks they have to carry out.
21
2.6 Data Analysis
The following Data Analysis is based on a sample of N=28 respondents and gives an insight
into the relationship between personality scores and user's tendency to fall for the Active User
Paradox. The variables that are used for this analysis are the 3 Personality Scales (GEX, NCS,
Computer Anxiety), and the Challenge seeking and explorative behavior variables that
represent the tendency to fall for the AUP. For every respondent these 5 scores were obtained.
It appears that there was no significant variance for the WORD tasks so that these scores were
not relevant for the experiment. Therefore, the AUP scores are only calculated on the basis of
the GIMP tasks.
The AUP scores were calculated through using the following variables: set parameter
amount, method diversity, read handout duration, undo amount, mean specificity, mean
difficulty, mean complexity, mean delayed feedback and the mean parameter demands. After
scoring these variables, the scores were z-standardized and then average scores for
exploratory behavior and challenge seeking behavior are calculated on a range from -1 to 1.
This means that people’s resistance to fall for the AUP can be measured on a challenge
seeking- and an explorative behavior level so that these 2 variables calculated for the
measurement of the AUP.
With the 3 personality variables and the 2 AUP variables, an explorative analysis was
carried out first to get an overview of the distribution of the personality variables (GEX, NCS,
Anxiety) as well as the AUP variables (Challenge seeking, Explorative behavior). Besides, a
descriptive analysis of the 5 variables gives information about the demographic data.
After that, the consistency of the scales was tested through a reliability analysis.
Therefore, for each scale Cronbach’s alpha was calculated.
To test the hypotheses the correlations between the GEX, NCS, Anxiety scale and the
AUP variables are calculated with the correlation coefficient r.
3.Results
The results show the composition of the sample, as well as the distributions of the variables
and confirm some of the drawn hypotheses through showing correlations. The findings are
listed below.
3.1 Demographics
30 respondents participated in the study. As the following table shows, the sample consisted
of 16 female and 12 male respondents as the data of 2 respondents was not usable. The
average age was 23 years, ranging from 19 to 30 (SD=2.33).
22
Table 5. Demographic Data
Percent
M (SD)
Age
22.68 (2.33)
Gender
Male
42.9
Female
57.1
Note: M=Mean SD=Standarddeviation
3.2 Descriptives
With regard to their expertise, many participants rated their expertise with graphical programs
as low (M=2.53) while many described themselves as experts with Microsoft Word (M=4.25)
on a scale ranging from 0 to 5. The self-assessment of the expertise level for graphical
programs of the participants was very low (M=3.61) . The mean scores for people’s expertise
of certain graphical programs are listed in the table below.
Table 6. Descriptives Expertise
Min
Max
M (SD)
Exp_Microsoft_Paint
2
4
2.53 (0.69)
Exp_Adobe_Photoshop
1
5
1.82 (0.98)
Exp_MacPaint
1
3
1.11 (0.42)
Exp_GIMP
1
3
1.21 (0.49)
Exp_Paintbrush
1
2
1.11 (0.31)
Exp_Microsoft Word
2
5
4.25 (0.52)
Exp_Graphical programs
0
9
3.61 (1.91)
The mean scores of the personality scores indicate that the participants tend to have a
moderate tendency towards Geekism as the scores are at the middle of the scale (M=.01) and
also towards NCS (M=.12) while most of the participants seem not to be computer anxious
(M=-.38). Considering the AUP scores, people tend not to fall for the AUP as they have
challenge seeking behavior (-.01) while a moderate number of participants show explorative
behavior (M=.01).
23
Table 7. Descriptives character traits and AUP
M (SD)
GEX
.01 (0.29)
NCS
.12 (0.28)
CompAnx
AUP_explore
AUP_challenge
- .38 (0.25)
.01 (0.41)
- .01 (0.28)
Figure 3. Distribution of the variables
Through splitting the variables by gender, it can be seen that the the average score for computer anxiety was much lower for men (M=-0,50) than for women (M=-0,29). Furthermore,
mainly men scored high on the GEX scale (M=0,15) while women scored very low (M=-0,16)
showing not as strong tendencies towards geekism as men. Additionally, men also scored
much higher on the NCS scale (M=0,16) than women who scored at the center of the scale
(.01). On the explorative level of the AUP, men scored much higher (M=0,15) than women
(M=-0,17) showing that men showed much more explorative behavior than women. On the
24
challenge-seeking level of the AUP variable, both genders scored below the center of the
scale. These results can be seen in table and are illustrated in figure 5.
Table 8. Descriptives Variables, splitted by gender
Gender
Min
Max
M(SD)
female CompAnx
-.74
.11
-.29(.22)
GEX
-.46
.32
-.16(.18)
NCS
-.44
.46
.01(24)
AUP_explore
-.51
.24
-.17(.20)
AUP_challenge
-.41
.46
-.01(.21)
CompAnx
-.79
.08
-.50(.25)
GEX
-.67
.65
.15(.35)
NCS
-.22
.61
.16(.30)
AUP_explore
-.49
1.92
.15(.62)
AUP_challenge
-.44
.85
-.05(.39)
male
Figure 4. Variables splitted by gender
25
3.3 Hypotheses testing
The hypotheses were tested through calculating correlations with the correlation coefficient r.
Table 9. Correlations
Gex
NCS
ComAnx
AUP_explore
AUP_challenge
* p<0,05
** p<0,01
r
r
r
r
r
Gex
1
.55**
-.73**
.20
.25
NCS
ComAnx
.55**
-.73**
1
-.43*
-.43*
1
.12
-.20
.49**
-.24
AUP_explore
.20
.12
-.20
1
.10
AUP_challenge
.25
.49**
-.24
.10
1
At first, the hypothesis concerning geekism was investigated. The hypothesis states that a
high score on the geekism index is positively correlated with people’s tendency to resist the
AUP. A positive correlation between AUP_explore (r=.20) and geekism was found as well as
between AUP challenge and geekism (r=.25). These results indicate that people who score
high on geekism show explorative and challenge seeking behavior. However, we cannot
confirm this relation with sufficient certainty (p=0.31; p=.21). Besides, it should be noted that
geekism correlates positively (r=.55) and with strong certainty (p<0.01) with NCS, indicating
that these concepts share some similarities.
Figure 5. Correlation between Geekism and AUP
26
The second hypothesis that NCS is positively related with people’s resistance to the AUP was
tested. Here, a moderate to strong positive correlation between the AUP_challenge and NCS
was found (r=0,49) which can be predicted with strong certainty (p=.008). This means that
people with a high need for cognition tend to resist the AUP due to their challenge seeking
behavior. A weaker correlation was found between NCS and AUP_explore (r=.12). This leads
to the conclusion that people who score high on NCS show some kind explorative behavior
that increases their resistance to the AUP. We cannot confirm this relationship with high
certainty (p=.55).
Additionally, there was a strong negative correlation found between computer anxiety and
geekism (r=-.73) and a moderate negative correlation with NCS (r=-.43). These relationships
can be predicted with great certainty and prove that people scoring high on geekism and NCS
show only low computer anxiety.
Figure 6. Correlation between NCS and AUP
27
Finally, the third hypothesis, computer anxiety is negatively correlated with people’s
resistance to the AUP, was tested. This hypothesis was confirmed through finding a negative
correlation between AUP_explore (r=-0.20) and computer anxiety as well as between
AUP_challenge and computer anxiety (r=-0.24). This would lead us to the assumption that
people with great computer anxiety are not resistant to the AUP while low computer anxiety
can be seen as a predictor for high resistance to the AUP. But, we cannot predict this
relationship with great certainty (p=.31; p=.24).
Figure 7. Correlation between Computer anxiety and AUP
4. Discussion
The aim of the study was to investigate the relationship between people’s resistance to the
AUP and certain personality traits. The main results of the statistical analysis suggest that
people who score high on need-for-cognition have a better resistance to the AUP with regard
to their challenge-seeking behavior than others. This relationship can be predicted with great
certainty. Furthermore, a positive association between geekism and people’s resistance to the
AUP was found as well as a negative relation between Computer anxiety and people’s
28
resistance to the AUP but we can not be certain of these relationships.
In an overall assessment of the study, it can be said that the observations of the
experiment confirm the findings of Caroll and Rosson (1987). During the execution of the
tasks, we observed the production and assimilation bias as described by Caroll and Rosson
(1987). The production bias was observed when people want to solve the task but stick to old
known procedures instead of exploring new ones that would offer more effective and faster
ways of solving the tasks. This is described as motivational paradox (1987) as people want to
produce output but do not show the motivation to explore an efficient and fast way to produce
this output. This behavior was observed during a task where participants should remove
certain objects and used the eraser tool which is very time consuming while other more
effective tools like the color select and delete tool could be used. However, participants
preferred using the eraser tool as it was well known to them and easy to use. Even when they
had to solve many more tasks under the same schema, most participants stick to the old
known procedure and used the eraser.
Additionally, the assimilation bias (Carroll and Rosson, 1987) was observed in these
situations where people only apply what they already know to handle new situations. Carrol
and Rosson (1987) describe this phenomenon as a cognitive paradox where people interpret
situations from what they already know. For example, not many participants made the effort
to read in the provided handout about the functions of unknown tools. They rather stick into
the unknown and just try what is known to them. Consequently, most of them used the eraser
tool for removing objects which is not very effective. The observations show that these biases
appear when people do not invest enough effort to solve the task which leads them into
situation where they tend to fall for the AUP.
Out of these observations, we came to the conclusion that explorative- and challenge
seeking behavior, could increase people’s resistance to the AUP. Therefore we measured
people’s resistance to the AUP on an explorative- and challenge seeking level and looked at
associations with certain personality traits. In the following, the findings for each hypothesis
are described separately in more detail.
The first hypothesis (A high score on the geekism Index is positively related to
people's resistance to the AUP.) can not be confirmed with certainty by the results of the data
analysis. Considering contemporary literature, it was expected that there is a relationship
between geekism and the AUP. Due to Schmettow & Passlick (2013) geeks can be defined as
computer users with “the strong urge and endurance to understand the inner workings of a
29
computer system” which leads to a great affinity with the technological aspects of computers.
Furthermore, Schmettow (2013) argued that the “tendency to enjoy intellectual challenges
must be a precondition for geekism.”. These characteristics seem to be related to the Active
User Paradox as Carroll and Rosson (1982) assume that people who tend to fall for the AUP
do not make enough effort to read a manual first or try out new functions even if this would
help getting the task done faster and in a more efficient way. The intellectual abilities that are
supposed to be present at geeks place when it comes to technological computer aspects could
matter in this affair as they could increase the geeks resistance to the AUP. Therefore, it was
expected that geekism would have a positive impact on people’s resistance to the AUP.
Although a weak to moderate positive relation between geekism and the AUP for explorative
behavior and the AUP for challenge seeking behavior was found, we can not be very certain
of this relation.
One possible reason for this result may be fact that the sample did not cover many
people that could be characterized as geeks. Although the average score for geekism was
nearly in the middle of the scale (M=0,008), the variance shows that some people scored
much higher (see figure 4), indicating that the sample consisted of some people with geek
tendencies. Some scores were even above 0,5 which would show a strong predisposition for
geekism. Therefore it can be concluded that most of the participants scored at the middle of
the scale while some scores indicate strong geekish tendencies. This leads to the conclusion
that the sample contains participants that could be identified as geeks although this number
may be very low (see figure 4). Obviously, mainly male people could be regarded as geeks
because females mainly scored below average on the GEX scale (M=-0,15) while males
scored above average (M=0,15) (see table 4). This could lead to the assumption that a sample
with only male participants could have changed the results as stronger tendencies towards
geekism could have appeared so that the relationship may become stronger and of greater
certainty.
To find another explanation why the relationship between geekism and the AUP was
weak and not certain, we could have a closer look at the concept of geekism as it is a
relatively new concept and not much investigated yet. Therefore, we will take a comparable
concept of Carter (2011) into consideration that also seems to be linked to the AUP.
The GEX questionnaire is divided into 3 subscales that are motivational states,
values/attitudes and the behavior of Geeks (Sander & Schmettow, 2013). Carter et al. (2011)
present the concept of IT-mindfulness which has many similarities to the concept of Geeks,
although it seems to be more specific. With IT mindfulness Carter (2011) describes
30
consciousness awareness for the content and context of IT based routines that allow the user
to be flexible finding new ways of doing. Having a look at Carters conceptualization of IT
mindfulness, we come to know that he described it as a characteristic of people composed out
of four cognitive domains: 1) novelty producing, 2) novelty seeking 3) flexibility and 4)
engagement with the current situation (Carter et al., 2011). This classification is different from
that one of the geekism scale as carter divides his concept into 4 cognitive domains that are
more precise than those of the GEX scale. For example, the GEX subscale ‘motivational state’
is very broad while Carter has already defined the kinds of motivational states that are typical
for this population more clearly in categories as “novelty producing” and “novelty seeking”.
Here, he already makes a clear statement which kind of motivational states belong to people
with IT mindfulness. Furthermore, Carter also specifies the subcategory called “behavior” at
the GEX scale more clearly in his framework as he limits it to “flexibility within different
contexts”. The fourth category “engagement” of Carters framework may also be seen as a
further specialization of the subscale “attitude”. On its overall implications, the author
suggests that high levels of IT mindfulness reflect a tendency towards novelty seeking
behavior in the use of IT which could be positively related to an individual’s ability to deal
with IT applications in their work routines and therefore can be linked to the AUP. This could
lead to the assumption that the concept of IT mindfulness may be a better predictor for
people’s resistance to the AUP than geekism. However, after the comparison of the two
concepts, I come to the conclusion that the concept of IT mindfulness may be easier to
measure as it is more specified while it may be more difficult to measure the concept of
geekism as it is more complex. This does not imply that the concept of IT mindfulness is the
better one just because it is easier to measure. The concept of geekism comprises much more
different elements under his subscales than the concept of IT mindfulness which does not
have such a big scope due to its limited subcategories. This leads to the conclusion that the
concept of geekism may be broader but therefore it captures more people that could be
categorized as potential geeks than the concept of IT mindfulness captures people that could
be categorized as IT mindful. For the assessment of the relation between geekism and the
AUP, this means that the concept of geekism may be a better predictor for the AUP than the
concept of IT mindfulness. However, it must be noticed that there are no studies available
testing the concept of IT mindfulness regarding the AUP.
Besides the possibility that the concept could be decisive for the results, the possibility
that other variables influence the result must be taken into consideration. Having a look at the
rating for graphical expertise where participants should judge their capabilities themselves, it
31
is conspicuous that most participated rated themselves with a very low number. On a scale
from 0 to 10, the average score was M=3, 61(1,91). This could either indicate that most
participants are not familiar with graphical programs or they underrate their abilities. If the
latter was the case, then another variable would come into play: Self Confidence or rater selfefficacy. As Carter (2011) stated: “unless confidence is tempered by a degree of uncertainty,
openness to new information is likely to inhibited.”, meaning that low self-confidence or selfefficacy leads people to not being open for the processing of new information so that they do
not spend much effort to solve tasks. This could inhibit people’s explorative and challenge
seeking behavior and may be one further explanation why the results were not significant.
Regarding the second hypothesis (A high score on the NCS is positively correlated to
people's resistance to the AUP.), it is confirmed with great certainty by the results of the
statistical analysis. We found a moderate to strong positive correlation between Need for
Cognition and people’s resistance to the AUP on the challenge seeking level (r=.489). As need
for cognition measures the “tendency to engage in and enjoy thinking” (Cacioppo & Petty,
1982) or in other words degree to which people tend to engage in elaborative thought, it can
be assumed that people who score high on this dimension enjoy challenging activities. This is
associated with the assumption that persons with a low tendency for the AUP should show a
stronger will to master the task in the most appropriate way, which is observed as choice of
more specific, complex and difficult to use functions. This could explain why Need for
cognition and the AUP score for the challenge-seeking variable correlate. It can be concluded
that people who score high on the NCS scale have a higher resistance to the AUP with regard
to their challenge seeking qualities.
On the other hand, NCS did not show a strong correlation with the explore variable of
the AUP. It can be established that people who score high on the NCS scale did not show
many signs of explorative behavior that would be relevant to resist the AUP. However, during
the study we observe participants who showed explorative behavior. For example, when one
participant did not find the tool to color all blue objects green as demanded in the instruction
form, he discovered that he could use green stickers to cover the objects. He uses a green
sticker that had the form of a plant to cover all blue objects with that sticker. Here, the
participant showed very explorative behavior.
However, other variables may also be of great importance. One variable that is also
mentioned by Carter et al. (2011) is computer anxiety. Due to Carter, “someone who is overly
anxious is even more likely to be committed to a particular course of action“. Anxiety about
32
the implications of computer use such as the loss of important data or fear of other possible
mistakes could play an important role why people do not show explorative behavior. This
variable was further investigated within the following third hypothesis.
The third hypothesis (A High score on the Computer Anxiety Rating scale is
negatively correlated to people's resistance to the AUP.) can not be confirmed with certainty
by the results of the data-analysis. However, there was a negative correlation found between
Computer anxiety and people’s resistance to the AUP. It could be expected that computer
anxiety is negatively associated with challenge-seeking and explorative behavior as anxiety
about the implications of computer use such as the loss of important data or fear of other
possible mistakes could inhibit people’s choices. Many participants told during the tasks that
they are scared to do something wrong and after the tasks some participants also reported that
they did not explore a lot or try new tools as they were scared to make mistakes. Some
participants were also scared that it would take too much time to read the handbook or explore
with new functions even if they were told that they have enough time. These statements
would confirm the third hypothesis that a high level of computer anxiety leads to lower
resistance to the AUP as participants were not explorative or challenge seeking when they
were scared to do something wrong. This observation is confirmed through a weak negative
correlation with the AUP variables explore and challenge seeking.
Furthermore, it should be noticed that computer anxiety correlated strongly negative
with geekism. This relationship can be predicted with strong certainty (p<0,01). This leads to
the assumption that people who score high on the CARS have low tendencies towards
geekism. Consequently, geeks show low levels of computer anxiety meaning that one factor
that could influence the positive correlation between geekism and people’s resistance to the
AUP may be the level of computer anxiety.
One further negative correlation of which we can be very certain was found between
computer anxiety and NCS. This correlation shows that a high level of computer anxiety
inhibits people’s ability to explore things and this agrees with the findings about the AUP
which shows that low levels of NCS inhibit people’s resistance to the AUP.
Out of these findings it can be assumed that computer anxiety is a moderator variable
for predicting the relation between geekism and people’s resistance to the AUP and NCS and
people’s resistance to the AUP.
Within the framework of Carter (2011), computer anxiety is also related to the
concept of habit. Carter (2011) states that computer anxiety leads people to rely on well33
known procedures. This is connected to the assimilation bias that was described by Caroll and
Rosson (1982) where people stick to well-known procedures when confronted with an IT
problem instead of using advances in technology which would offer more efficient and faster
ways to deal with the problem. This leads the authors to the assumption that “habit is
negatively associated with an individual’s predisposition to create new applications of IT in
their work routines” (Carter et al., 2011) or in other words to fall for the AUP. The feeling of
anxiety when people get confronted with IT problems seems to have a negative influence on
flexible and adaptive behavior and therefore on habits because people who are very anxious
are more likely to stick with a particular course of action. So, the concept of computer anxiety
could be further invented and connected to habits to find significant results.
4.1 Limitations
The study at hand has several limitations and weak points. In the following, these will be
discussed.
At first, it should be said that the sample was composed only of psychology students
what could have limited the results. It could be the case that psychology students do not want
to invest too much effort in the exploration and operation of a graphical program as they
probably could not use this knowledge any further. Therefore, they maybe do not want to
spend much time with these matters as it would not help them during their further study. This
could explain why we did not observe much explorative behavior. It could be better to include
students from graphical or technical studies as they would probably like to explore more with
graphical programs. On the other hand, we probably found no variance within the word tasks
as students have to work with Word Processors like Word a lot, for example for their
homework or other academic assignments. Therefore, students are very familiar with the
functions of Word and this explains why almost all participants used the same procedures to
solve the tasks. Therefore, the results of the Word tasks could not help us predicting people’s
resistance to the AUP. Probably, the results would show greater variance with another
population that is not so trained with Word as students.
Secondly, the gender ratio could be decisive for the results. Especially when it comes
to IT based procedures, men tend to have a better understanding than women. This agrees
with the finding that mainly male participants scored high on geekism while female
participants scored low on geekism. Maybe the results would be of greater certainty if the
sample had only consisted of male participants as they show stronger tendencies towards
34
geekism which was found to be a positive predictor for people’s resistance to the AUP.
Thirdly, the translation of the Computer Anxiety Scale may have influence the results.
It was translated from its original language English into German by the researcher. As some
terms were outdated, it was hard to translate them into German as this could change their
meaning. For example, the first item “I feel insecure about my ability to interpret a computer
printout” was changed into “Ich fühle mich unsicher im Bezug auf meine Fähigkeit einen
Computer Ausdruck zu interpretieren”. The word “computer printout” is hard to translate and
not up-to-date so it turned out that many participants did not know how to interpret this item
in the right way. So, they often asked what was meant by this item. However, it is hard to
change words so that they appear recent without changing the meaning.
Fourthly, the AUP assessment could be improved.. The formulation of the instructions
could be made clearer, for example when the instruction says “color all blue objects green”,
this does not exclude that the background could also be colored green but there are no clear
scoring patterns for those special cases yet. What could be emphasized positively is that the
images of the GIMP tasks contain one object which was harder to color than the other ones.
Having tasks of varying difficulty could show differences in participant’s abilities.
4.2 Future Research
This study is only a first step in the investigation of personality traits and people’s resistance
to the AUP. Within this study, only the character traits geekism, Need for Cognition and
Computer Anxiety were investigated. Obviously, other variables could be of great importance
when it comes to people’s resistance to the AUP. Carter et al. (2011) have presented a helpful
framework to unravel the Active User Paradox. This framework shows similarities to geekism
and need for cognition and could give interesting implications for further research in this area.
4.3 Conclusion
In summary, this study successfully investigated the relation between certain personality traits
and the AUP. A significant positive relation was found between Need for Cognition and the
AUP, meaning that people with a high level of Need for Cognition tend to resist the AUP
better than others. One further certain relation was found between computer anxiety and
geekism as well as between Computer anxiety and NCS. This gives the impression that
computer anxiety functions as moderator variable in the relationships between geekism and
the AUP and NCS and the AUP. Additionally, there were correlations found between geekism
and the AUP and Computer Anxiety and the AUP but we can not be certain of these relations.
Considering these results, it can be concluded that users differ in how much effort they invest
35
to resist the AUP as users with a high need for cognition invest more than others and could
resist the AUP better.
Although there were no significant relations found between geekism and Need for
Cognition and the AUP, this does not necessarily mean that there are no relations. It has been
established that several limitations could have influenced the results and thus further research
is necessary to gain a more secure evidence base for the results.
36
References
Barbeite, F. G., & Weiss, E. M. (2004). Computer self-efficacy and anxiety scales for an
internet sample: Testing measurement equivalence of existing measures and
development of new scales. Computers in Human Behavior, 20, 1–15.
doi:10.1016/S0747-5632(03)00049-9
Bhavnani, S. K., & John, B. E. (2000). The Strategic Use of Complex Computer Systems.
Human-Computer Interaction, 15, 107–137. doi:10.1207/S15327051HCI1523_3
Cacioppo, J. T., & Petty, R. E. (1982). The need for cognition. Journal of Personality and
Social Psychology. Doi:10.1037/0022-3514.42.1.116
Carroll, J. M., & Rosson, M. B. (1987). Paradox of the active user. In J. M. Carroll (Ed.),
Interfacing Thought (pp. 80–111). MIT Press. Retrieved from
http://portal.acm.org/citation.cfm?id=28451
Carter, M., Clements, J. a, Thatcher, J., & George, J. (2011). Unraveling the “ paradox of the
active user ”: Determinants of individuals ’ innovation with itbased work routines.
AMCIS 2011 Proceedings. Retrieved from
http://aisel.aisnet.org/amcis2011_submissions/41
Fu, W. T., & Gray, W. D. (2004). Resolving the paradox of the active user: Stable suboptimal
performance in interactive tasks. Cognitive Science, 28(6), 901–935.
doi:10.1016/j.cogsci.2004.03.005
Heinssen, R. K., Glass, C. & Knight L. (1987). Assessing Computer Anxiety: Development
and Validation of t he Computer Anxiety Rating Scale. Computers in Human behavior ,
3, 49-59
Nielsen, J. (1998). Paradox of the Active User. Nielsen Norman Group. Retrieved from
http://www.nngroup.com/articles/paradox-of-the-active-user/
O’Brien, B. (2007). Gifted geeks: The emergence and development of computer technology
talent. University of Kansas. Retrieved from
http://gradworks.umi.com/32/67/3267198.html
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Sam, H. K., Othman, A. E. A., & Nordin, Z. S. (2005). Computer self-efficacy, computer
anxiety, and attitudes toward the Internet: A study among undergraduatesin Unimas.
Educational Technology and Society, 8, 205–219.
Schmettow, M., & Drees, M. (2014). What drives the geeks ? Linking computer enthusiasm to
achievement goals. In Proceedings of BCS HCI 2014 - Sand, sea and Sky – Holiday
HCI. Southport, UK.: BCS Learning and Development Ltd.
Schmettow, M., & Keil, J. (2013). Development of an Implicit Picture Story Exercise
Measuring Personal Motives for the Interaction with Technical Products. University
of Twente.
Schmettow, M., Noordzij, M. L., & Mundt, M. (2013). An implicit test of UX: Individuals
Differ in What They Associate with Computers. In CHI ’13 Extended Abstracts on
Human Factors in Computing Systems on - CHI EA '13 (pp. 2039 – 2048). New York,
New York, USA: ACM Press. doi:10.1145/2468356.2468722
Schmettow M. & Passlick, F. (2013). Being Geek – An attempt at building a theory of
geekism. University of Twente
Schmettow, M. & Sander, N. (2013). The construction and evaluation of a questionnaire
measuring geekism. University of Twente.
White, G. L., Ph, D., Sivitanides, M. P., & Marcos, S. (1997). A Theory of the Relationships
between Cognitive Requirements of Computer Programming Languages and
Programmers ’ Cognitive Characteristics, 13(1), 59–66.
38
Appendix
Appendix 1. Gimp Task 3
39
Appendix 2. Experiment Material (German version) and Experiment Material (Dutch Version)
including the questionnaires GEX, NCS and CARS
GW.07.130
EINWILLIGUNG NACH AUFKLÄRUNG
Ich, …………………………………………………………….. (Name des Respondenten)
willige ein, an einer Untersuchung mitzumachen, die durchgeführt wird von
Julian Ebelhäuser & Wiebke Stöhr
Ich bin mir bewusst, dass die Teilnahme an dieser Untersuchung freiwillig ist. Ich kann meine
Teilnahme jederzeit beenden und die Daten, die sich aus der Untersuchung ergeben,
zurückbekommen oder löschen.
Die folgenden Punkte wurden mir erklärt:
1.
2.
3.
4.
5.
Das Ziel dieser Untersuchung ist es Einsicht in die Nutzungsmöglichkeiten von
Nutzeroberflächen von Programmen zu bekommen.
Meine Aufgabe wird es sein, unterschiedliche Fragebögen auszufüllen und
verschiedene Aufgaben mit den Programmen GIMP und Microsoft Word auszuführen.
Die gesamte Untersuchung wird ungefähr 120 Minuten dauern. Am Ende wird der
Untersucher erklären, worum die Untersuchung ging.
Teilnahme an dieser Untersuchung sollte keinen Stress oder Unbehagen hervorrufen.
Die Daten, die sich aus der Untersuchung ergeben, werden anonym verarbeitet und
können darum nicht mit meinem Namen in Verbindung gebracht werden.
Der Untersucher wird alle weiteren Fragen zur Untersuchung jetzt oder im weiteren
Verlauf beantworten.
Für eventuelle Beschwerden über diese Untersuchung können Sie sich an die Schriftführerin
der ethischen Kommission der verhaltenswissenschaftlichen Fakultät der Universität Twente
Frau J. Rademaker wenden. (Telefon: 053-4894591; e-mail:[email protected],
Postfach 217, 7500 AE Enschede).
Unterschrift Untersucher: ……………………………………
Datum: …………………..
Unterschrift Respondent: ……………………………………
Datum: …………………..
40
Geschlecht:___________
Alter: ___________
Bitte ankreuzen, wie oft du die folgenden Programme bisher benutzt hast. (nur ein Kreuz pro
Zeile)
noch nie
selten
manchmal
oft
täglich
Microsoft Paint
O
O
O
O
O
Adobe Photoshop
O
O
O
O
O
MacPaint
O
O
O
O
O
GIMP
O
O
O
O
O
Paintbrush
O
O
O
O
O
Wie bewertest du deine bisherige Erfahrung mit Grafikprogrammen allgemein auf einer Skala
von 0 (überhaupt keine Vorkenntnisse) bis 10 (sehr viel Erfahrung)?
___________
41
Aufgabenteil 1 (GIMP)
1)

Öffne die Datei task 1 version 1.

Entferne alle roten Objekte im Bild, versuche die anderen Objekte so wenig
wie möglich zu beschädigen.

Speichere das Bild.
2)


Entferne alle grünen Objekte im Bild, versuche die anderen Objekte so wenig

Speichere das Bild.
3)


Entferne alle violetten Objekte im Bild, versuche die anderen Objekte so wenig wie möglich zu beschädigen.

Speichere das Bild.
4)


Entferne alle blauen Objekte im Bild, versuche die anderen Objekte so wenig

Speichere das Bild.
5)
42


Entferne alle grünen Objekte im Bild, versuche die anderen Objekte so wenig

Speichere das Bild.
Sind alle Aufgaben bis hier abgeschlossen, so wende dich an den Experimentleiter.
43
1)


Wähle einen grünen Farbton und färbe alle blauen Objekte im Bild in dieser
Farbe ein.

Speichere das Bild.
2)


Wähle einen blauen Farbton und färbe alle orangenen/braunen Objekte im
Bild in dieser Farbe ein.

Speichere das Bild.
3)


Wähle einen roten Farbton und färbe alle gelben Objekte im Bild in dieser
Farbe ein.

Speichere das Bild.
4)


Wähle einen grünen Farbton und färbe alle pinken/violetten Objekte im Bild
in dieser Farbe ein.

Speichere das Bild.
5)

44

Wähle einen blauen Farbton und färbe alle braunen Objekte im Bild in dieser
Farbe ein.

Speichere das Bild.
45
1)


Entferne alle Balken, versuche die roten Kreise und Sterne so wenig wie möglich zu beschädigen.

Speichere das Bild.
2)


Entferne alle Balken, versuche die blauen Kreise und Sterne so wenig wie
möglich zu beschädigen.

Speichere das Bild.
3)


Entferne alle Balken, versuche die grünen Kreise und Sterne so wenig wie

Speichere das Bild.
4)


Entferne alle Balken, versuche die gelben Kreise und Sterne so wenig wie

Speichere das Bild.
5)

46

Entferne alle Balken, versuche die orangenen Kreise und Sterne so wenig wie

Speichere das Bild.
47
Aufgabenteil 4 (Microsoft Word)
Das geöffnete Textdokument enthält Text von Wikipedia.org. Hyperlinks im Text sind mit
blauer Schriftfarbe gekennzeichnet.
1)
Verändere alle Hyperlinks im ersten Absatz, sodass sie unterstrichen, fett, in
der Schriftart Times New Roman und mit roter Schriftfarbe formatiert sind.
2)
Verändere alle Hyperlinks im zweiten Absatz, sodass sie unterstrichen, fett, in
der Schriftart Times New Roman und mit grüner Schriftfarbe formatiert sind.
3)
Verändere alle Hyperlinks im dritten Absatz, sodass sie unterstrichen, fett, in
der Schriftart Times New Roman und mit gelber Schriftfarbe formatiert sind.
4)
Verändere alle Hyperlinks im vierten Absatz, sodass sie unterstrichen, fett, in
der Schriftart Times New Roman und mit orangener Schriftfarbe formatiert sind.
5)
Verändere alle Hyperlinks im fünften Absatz, sodass sie unterstrichen, fett, in
der Schriftart Times New Roman und mit violetter Schriftfarbe formatiert sind.
6)
Verändere alle Textüberschriften, sodass sie fett, in der Schriftart Times New
Roman, in der Schriftgröße 12 und in schwarzer Schriftfarbe formatiert sind. Füge außerdem eine Nummerierung (z.B. "1. First paragraph") hinzu.
7)
Speichere das Textdokument.
Nach Fertigstellung der obigen Aufgaben bitte umblättern.
48
Bitte ankreuzen, wie oft du Microsoft Word bisher benutzt hast. (nur ein Kreuz)
noch nie
selten
manchmal
oft
täglich
O
O
O
O
O
Auf den nächsten Seiten folgen drei Fragebögen. Fülle diese bitte aus.
49
Geben sie für jede Aussage an, in wie fern sie auf Sie zutrifft.
Ich würde komplizierte Probleme einfachen
Problemen vorziehen.
Völlig un-
O
O O O O O O Trifft voll
und ganz
zutreffend
zu
Ich trage gerne die Verantwortung für eine
Völlig
Situation, die sehr viel Denken erfordert.
unzutreffend
O
und ganz
zu
Denken entspricht nicht dem, was ich unter
Spaß verstehe.
Völlig
O
unzutreffend
und ganz
zu
Ich würde lieber etwas tun, das wenig Denken
erfordert, als etwas, das mit Sicherheit meine
Denkfähigkeit heraus fordert
Völlig
O
unzutreffend
und ganz
zu
Ich versuche, Situationen vorauszuahnen und
zu vermeiden, in denen die Wahrscheinlichkeit
groß ist, dass ich intensiv über etwas nachdenken muss.
Völlig
Ich finde Befriedigung darin, angestrengt und
stundenlang nachzudenken.
Völlig
O
unzutreffend
und ganz
zu
O
unzutreffend
und ganz
zu
Ich denke nur so viel, wie ich muss.
Völlig
O
unzutreffend
und ganz
zu
Ich denke lieber über kleine, alltägliche
Vorhaben nach, als über langfristige.
Völlig
O
unzutreffend
und ganz
zu
Ich mag Aufgaben, die, wenn ich sie einmal
erlernt habe, wenig Nachdenken erfordern.
Völlig
unzutreffend
O
und ganz
zu
50
Die Vorstellung, mich auf mein Denkvermögen
zu verlassen, um es zu etwas zu bringen,
spricht mich an.
Völlig un-
O
zutreffend
und ganz
zu
Die Aufgabe, neue Lösungen für Probleme zu
finden, macht mir wirklich Spaß.
Völlig
O
unzutreffend
und ganz
zu
Ich finde es nicht sonderlich aufregend, neue
Denkweisen zu lernen.
Völlig
O
unzutreffend
und ganz
zu
Ich habe es gern, wenn mein Leben voller
kniffliger Aufgaben ist, die ich lösen muss.
Völlig
O
unzutreffend
und ganz
zu
Abstrakt zu denken reizt mich.
Völlig
O
unzutreffend
und ganz
zu
Ich würde lieber eine Aufgabe lösen, die
Intelligenz erfordert, schwierig und bedeutend
ist, als eine Aufgabe, die zwar irgendwie
wichtig ist, aber nicht viel Nachdenken erfordert.
Völlig
Wenn ich eine Aufgabe erledigt habe, die viel
geistige Anstrengung erfordert hat, fühle ich
mich eher erleichtert als befriedigt.
Völlig
O
unzutreffend
und ganz
zu
O
unzutreffend
und ganz
zu
Es genügt, dass etwas funktioniert, mir ist es
egal, wie oder warum.
Völlig
O
unzutreffend
und ganz
zu
Normalerweise denke ich intensiv über
Sachen nach, selbst wenn diese mich nicht
persönlich betreffen.
Völlig
unzutreffend
O
voll
O O O O O O Trifft
und ganz
zu
Die folgenden Aussagen enthalten Begriffe wie “Computer“ oder „technische Apparate“.
Bitte denken Sie dabei auch an Laptops, Smartphones, Tablets und andere technische
Geräte.
Falls Ihnen eine Frage unklar ist, oder sie aus anderen Gründen keine Antwort geben
können oder wollen, lassen Sie diese Frage einfach unbeantwortet.
1
Ich möchte verstehen, wie
Computerteile oder Software
funktionieren.
2
Wenn jemand Hilfe mit dem
Computer braucht, versuche ich so
gut wie möglich zu helfen.
3
Privatsphäreeinstellungen am
Computer oder im Internet ist sehr
wichtig für mich.
4
Komplizierte Vorgänge mit
technischen Geräten schrecken
mich ab.
5
Ich habe schon einmal technische
Geräte zweckentfremdet oder
modifiziert.
6
Objektivität ist wichtig für mich.
7
Ich habe nicht das Gefühl, viel
Kontrolle über meine technischen
Geräte zu haben.
8
In meiner Freizeit verbringe ich
nicht mehr Zeit am Computer oder
anderen technischen Geräten als
andere Menschen.
Wenn ich mir ein neues
Computergerät kaufe, ist mir die
Leistung wichtiger als die äußere
Erscheinung.
Es motiviert mich, technische
Geräte zu optimieren oder an
meine Wünsche anzupassen.
1
8
1
9
2
0
Ich habe schon einmal ein Projekt
oder eine Arbeit von mir frei ins
Internet gestellt, bzw. würde dies
tun.
Trifft auf
mich
überhaupt
nicht zu
Trifft auf
mich
überhaupt
nicht zu
Trifft auf
mich
überhaupt
nicht zu
Trifft auf
mich
überhaupt
nicht zu
Trifft auf
mich
überhaupt
nicht zu
Trifft auf
mich
überhaupt
nicht zu
Trifft auf
mich
überhaupt
nicht zu
Trifft auf
mich
überhaupt
nicht zu
Trifft auf
mich
überhaupt
nicht zu
Trifft auf
mich
überhaupt
nicht zu
Trifft auf
mich
überhaupt
nicht zu
O O O O O O O Trifft auf
mich
vollkomme
n zu
mich
vollkomme
n zu
mich
vollkomme
n zu
mich
vollkomme
n zu
mich
vollkomme
n zu
mich
vollkomme
n zu
mich
vollkomme
n zu
mich
vollkomme
n zu
mich
vollkomme
n zu
mich
vollkomme
n zu
mich
vollkomme
n zu
2
1
Ich denke es gibt Menschen, die
mich einen Computerfreak nennen
würden.
mich
vollkomme
n zu
mich
vollkomme
n zu
mich
vollkomme
n zu
mich
vollkomme
n zu
mich
vollkomme
n zu
mich
vollkomme
n zu
mich
vollkomme
n zu
9
Ich bin interessiert an technischen
Produkten, welche vielseitig
einsetzbar sind.
Trifft auf
mich
mich
überhaupt
vollkomme
nicht zu
n zu
1
0
Ich investiere viel Zeit und Mühe
damit, Dinge mit
Computergeräten/Software
auszuprobieren.
Trifft auf
mich
mich
überhaupt
vollkomme
nicht zu
n zu
11
Es ist wichtig, dass sich jeder
Gedanken macht, was er ins
Internet hochläd und was nicht.
Trifft auf
mich
mich
überhaupt
vollkomme
nicht zu
n zu
1
2
Ich eigne mir gerne Wissen
bezüglich technischen Geräten
(Hardware/Software) an.
Trifft auf
mich
mich
überhaupt
vollkomme
nicht zu
n zu
2
2
2
3
2
4
2
5
2
6
2
7
Trifft auf
mich
überhaupt
nicht zu
Das Innenleben technischer Geräte Trifft auf
oder das Programmieren von
mich
Software interessiert mich nicht.
überhaupt
nicht zu
Ich vermeide die erweiterten
Trifft auf
Optionen meiner technischen
mich
Geräte.
überhaupt
nicht zu
Ich teile gerne meine Ideen und
Trifft auf
Projekte mit anderen.
mich
überhaupt
nicht zu
Herausfordernde Aufgaben an
Trifft auf
technischen Geräten reizen mich.
mich
überhaupt
nicht zu
Ich verfüge über ein großes
Trifft auf
Wissen, was Computergeräte
mich
betrifft (Hardware/Software).
überhaupt
nicht zu
Ich versuche so wissenschaftlich
Trifft auf
wie möglich an Dinge
mich
heranzugehen.
überhaupt
nicht zu
1
3
Ich habe schon des Öfteren
technische Geräte geöffnet, um zu
sehen, wie diese von innen
aussehen.
Trifft auf
mich
mich
überhaupt
vollkomme
nicht zu
n zu
1
4
Mir ist es wichtig, dass Menschen
freien Zugang zu meinen Projekten
oder Arbeiten haben.
Trifft auf
mich
mich
überhaupt
vollkomme
nicht zu
n zu
1
5
Mir gefällt es, technische Geräte
genau so steuern zu können, wie
ich es möchte.
Trifft auf
mich
mich
überhaupt
vollkomme
nicht zu
n zu
1
6
Technische Geräte verwende ich
teilweise anders als
vorhergesehen.
Trifft auf
mich
mich
überhaupt
vollkomme
nicht zu
n zu
1
7
Ich finde es toll, dass sich
Computerbenutzer gegenseitig bei
Problemen helfen, z.B. auf
Webforen.
Trifft auf
mich
mich
überhaupt
vollkomme
nicht zu
n zu
2
8
Viele Einstellungsmöglichkeiten an
technischen Geräten finde ich
abschreckend.
Trifft auf
mich
mich
überhaupt
vollkomme
nicht zu
n zu
2
9
Wenn es Probleme mit technischen Trifft auf
Geräten gibt, muss mir meistens
mich
mich
jemand anderes helfen.
überhaupt
vollkomme
nicht zu
n zu
3
0
Ein technisches Produkt muss für
mich schön aussehen.
3
1
Ich mag technische Geräte, die
Trifft auf
sehr viele verschiedene Funktionen mich
mich
haben.
überhaupt
vollkomme
nicht zu
n zu
3
2
Ich investiere viel Zeit und Mühe
damit, Dinge mit
Computergeräten/Software
auszuprobieren.
Trifft auf
mich
mich
überhaupt
vollkomme
nicht zu
n zu
3
3
Ich achte sehr bewusst auf den
Umgang meiner eigenen Daten
bezüglich der Privatsphäre.
Trifft auf
mich
mich
überhaupt
vollkomme
nicht zu
n zu
Trifft auf
mich
mich
überhaupt
vollkomme
nicht zu
n zu
3
4
Mein Studium/meine Arbeit hat viel
mit der Technik von Computern
oder mit Software zu tun
Trifft auf
mich
mich
überhaupt
vollkomme
nicht zu
n zu
Geben Sie für jede Aussage an, inwiefern sie auf Sie zu trifft.
1.
Während des Arbeitens mit Computerprogrammen bewerkstellige ich nur die Aufgaben, die für mich in der Situation relevant sind.
Trifft auf
mich
überhaupt
nicht zu
O
O
O
O
O
O
O
Trifft auf
mich
vollkommen
zu
2.
Es stört mich, wenn ich mit einem bestimmten Computerprogramm eine Aufgabe
nicht gelöst bekomme.
Trifft auf
mich
überhaupt
nicht zu
O
O
O
O
O
O
O
Trifft auf
mich
vollkommen
zu
3.
Während des Arbeitens mit dem Computer benutze ich nur die Funktionen die mir
beim Lösen einer Aufgabe helfen
Trifft auf
mich
überhaupt
nicht zu
4.
tige.
O
O
O
O
O
O
O
Trifft auf
mich
vollkommen
zu
Ich bin frustriert wenn ich für das Lösen einer Aufgabe mehr als ein Programm benö-
Trifft auf
mich
überhaupt
nicht zu
O
O
O
O
O
O
O
Trifft auf
mich
vollkommen
zu
5.
Bei der Verwendung von Computerprogrammen ist es mir wichtig, meine Aufgaben
auf möglichst geschickte Art und Weise zu lösen.
Trifft auf
mich
überhaupt
nicht zu
O
O
O
O
O
O
O
Trifft auf
mich
vollkommen
zu
6.
Bei der Verwendung von Computerprogrammen ist es mir wichtig, schnell und einfach zu Ergebnissen zu kommen.
Trifft auf
mich
überhaupt
nicht zu
O
O
O
O
O
O
O
Trifft auf
mich
vollkommen
zu
7.
Je schneller ich eine Aufgabe mit einem Computerprogramm bewerkstelligen konnte,
desto zufriedener bin ich.
Trifft auf
mich
überhaupt
nicht zu
O
O
O
O
O
O
O
Trifft auf
mich
vollkommen
zu
Entscheide für jede der folgenden Aussagen ob du Ihr zustimmst oder nicht und gebrauche dafür die
folgende 5 Punkte Skala. Die Skala reicht von „Ich stimme zu“ bis „Ich stimme nicht zu“. Fülle
eine Zahl von 1-5 neben die Statements ein, die deine Haltung zu dem Statement am besten
widerspiegelt.
Ich stimme zu
1
Ich stimme nicht zu
2
3
4
5
1. Ich fühle mich unsicher im Bezug auf meine Fähigkeit einen Computerausdruck zu
interpretieren.
2. Ich freue mich darauf während meiner Arbeit einen Computer zu benutzen.
3. Ich denke nicht, dass ich dazu fähig wäre eine Computerprogrammer Sprache zu
erlernen.
4. Die Herausforderung etwas über Computer zu lernen ist sehr aufregend für mich.
5. Ich bin zuversichtlich, dass ich mir auch anspruchsvolle Computerfähigkeiten
aneignen kann.
6. Jeder kann lernen einen Computer zu bedienen, wenn er geduldig und motiviert ist.
7. Lernen mit Computern umzugehen ist wie eine neue Fähigkeit zu erlernen – Je mehr
du übst, desto besser wirst du.
8. Ich habe Angst davor, dass ich vom Computer abhängig werde und mein logisches
Denken vernachlässige, wenn ich damit Computer zu viel benutze.
9. Ich bin mir sicher, dass ich mit der Zeit und Übung so gut im Umgang mit Computer
werde, wie ich es im Umgang mit anderen technologischen Geräten bin.
10. Ich fühle mich dazu im Stande, mit den Fortschritten die sich im Computerbereich ereignen
umgehen zu können.
11. Ich mag es nicht mit Maschinen zu arbeiten die schlauer scheinen als ich.
12. Ich fühle mich nicht wohl dabei, Computer zu benutzen.
13. Ich habe Schwierigkeiten damit, die technischen Aspekte von Computern zu
verstehen.
14. Es macht mir Angst daran zu denken, dass ich dafür verantwortlich sein könnt könnte
eine große Datenmenge auf dem Computer zu löschen durch das Drücken der falschen
Taste.
15. Ich weigere mich einen Computer zu benutzen weil ich Angst habe Fehler zu machen,
die ich dann nicht korrigieren kann.
16. Du musst ein Genie sein um alle Fähigkeiten des Computers zu verstehen.
17. wenn ich die Möglichkeit bekäme, würde ich gerne mehr über den Computergebrauch
lernen.
18. Ich meide Computer, weil sie mir nicht vertraut sind und mich einschüchtern.
19. Ich finde, dass Computer sowohl in Bildungseinrichtungen als auch im Arbeitsfeld
notwendig sind.
GW.07.130
GEÏNFORMEERDE TOESTEMMING
Ik, …………………………………………………………….. (naam proefpersoon)
stem toe mee te doen aan een onderzoek dat uitgevoerd wordt door
Julian Ebelhäuser & Wiebke Stöhr
Ik ben me ervan bewust dat deelname aan dit onderzoek geheel vrijwillig is. Ik kan mijn
medewerking op elk tijdstip stopzetten en de gegevens verkregen uit dit onderzoek terugkrijgen,
laten verwijderen uit de database, of laten vernietigen.
De volgende punten zijn aan mij uitgelegd:
1. Het doel van dit onderzoek is inzicht te krijgen in hoe interfaces van programma's gebruikt
kunnen worden.
2. Er zal van mij gevraagd worden om verschillende vragenlijsten in te vullen en verschillende
taken met de programma's GIMP en Microsoft Word uit te voeren.
Het hele onderzoek zal ongeveer 120 minuten duren. Aan het einde van het onderzoek zal de
onderzoeker uitleggen waar het onderzoek over ging.
3. Er behoort geen stress of ongemak voort te vloeien uit deelname aan dit onderzoek.
4. De gegevens verkregen uit dit onderzoek zullen anoniem verwerkt worden en kunnen daarom
niet bekend gemaakt worden op een individueel identificeerbare manier.
5. De onderzoeker zal alle verdere vragen over dit onderzoek beantwoorden, nu of gedurende
het verdere verloop van het onderzoek.
Voor eventuele klachten over dit onderzoek kunt u zich wenden tot de secretaris van de Commissie
Ethiek van de faculteit Gedragswetenschappen van de Universiteit Twente, mevr. J. Rademaker
(telefoon: 053-4894591; e-mail:[email protected], Postbus 217, 7500 AE Enschede).
Handtekening onderzoeker: ……………………………………
Datum: …………………..
Handtekening proefpersoon: ……………………………………
Datum: …………………..
Geslacht:___________
Leeftijd: ___________
AUB aankruisen hoe vaak je de volgende programma's tot nu toe gebruikt hebt (maar een kruis per regel)
nooit
zelden
soms
vaak
dagelijks
Microsoft Paint
O
O
O
O
O
Adobe Photoshop
O
O
O
O
O
MacPaint
O
O
O
O
O
GIMP
O
O
O
O
O
Paintbrush
O
O
O
O
O
Hoe beoordeel je jouw kennis van grafiek programmas op een schaal van 0 (helemaal geen voorkennis) tot
10 (heel veel kennis)?
___________
Opgaven onderdeel 1 (GIMP)
1)



Open het bestand task 1 version 1.
Verwijder alle roode objecten in de afbeelding, probeer hierbij andere objecten mogelijk
weinig te beschadigen.
Sla het bestand op.
2)



Verwijder alle groene objecten in de afbeelding, probeer hierbij andere objecten mogelijk
Sla het bestand op.
3)



Verwijder alle violette objecten in de afbeelding, probeer hierbij andere objecten mogelijk
Sla het bestand op.
4)



Verwijder alle blauwe objecten in de afbeelding, probeer hierbij andere objecten mogelijk
Sla het bestand op.
5)



Verwijder alle groene objecten in de afbeelding, probeer hierbij andere objecten mogelijk
Sla het bestand op.
Als je alle opgaven tot hier hebt afgesloten, dan informeer de experiment leider.
1)



Kies een groene kleur en maak alle blauwe objecten in de afbeelding groen.
Sla het bestand op.



Kies een blauwe kleur en maak alle oranje/bruine objecten in de afbeelding blauw.
Sla het bestand op.



Kies een roode kleur en maak alle gele objecten in de afbeelding rood.
Sla het bestand op.



Kies een groene kleur en maak alle pinke/violette objecten in de afbeelding groen.
Sla het bestand op.



Kies een blauwe kleur en maak alle bruine objecten in de afbeelding blauw.
Sla het bestand op.
2)
3)
4)
5)
1)



Verwijder alle streepjes in de afbeelding. Probeer hierbij de roode rondjes en sterren
mogelijk weinig te beschadigen.
Sla het bestand op.
2)



Verwijder alle streepjes in de afbeelding. Probeer hierbij de blauwe rondjes en sterren
Sla het bestand op.
3)



Verwijder alle streepjes in de afbeelding. Probeer hierbij de groene rondjes en sterren
Sla het bestand op.
4)



Verwijder alle streepjes in de afbeelding. Probeer hierbij de gele rondjes en sterren
Sla het bestand op.
5)



Verwijder alle streepjes in de afbeelding. Probeer hierbij de oranje rondjes en sterren
Sla het bestand op.
Opgaven onderdeel 4 (Microsoft Word)
Het geopende test bestand bevat een tekst van Wikipedia.org. Hyperlinks in de tekst zijn in blauw
gemarkeerd.
1) Verander alle hyperlinks in de eerste alinea, zodat ze onderstrepen, vet, in het lettertype Times
New Roman en met een roode kleur geformatteerd zijn.
2) Verander alle hyperlinks in de tweede alinea, zodat ze onderstrepen, vet, in het lettertype Times
New Roman en met een groene kleur geformatteerd zijn.
3) Verander alle hyperlinks in de derde alinea, zodat ze onderstrepen, vet, in het lettertype Times
New Roman en met een gele kleur geformatteerd zijn.
4) Verander alle hyperlinks in de vierde alinea, zodat ze onderstrepen, vet, in het lettertype Times
New Roman en met een oranje kleur geformatteerd zijn.
5) Verander alle hyperlinks in de vijfde alinea, zodat ze onderstrepen, vet, in het lettertype Times
New Roman en met een violette kleur geformatteerd zijn.
6) Verander alle opschriften zodat ze vet, in de lettertype Times New Roman, in tekengrootte 12 en
zwarte kleur geformatteerd zijn. Voeg verder een numering (b.v. "1. First paragraph") toe.
7) Sla het text bestand op.
Als je alle opgaven tot hier hebt afgesloten, sla dan om naar de volgende bladzijde.
AUB aankruisen hoe vaak je Microsoft Word tot nu toe hebt gebruikt (maar een kruis)
nooit
zelden
soms
vaak
dagelijks
O
O
O
O
O
Op de volgende pagina's vind je enkele vragenlijsten. Vul deze AUB in.
In hoeverre zijn de onderstaande uitspraken op jou van toepassing?
Als ik moet kiezen heb ik liever een
ingewikkeld dan een simpel probleem.
probleem.
O O O O O O O Helemaal
Helemaal
niet op mij
wel op mij
vvantoepassing
van
van toepassing
Ik ben graag verantwoordelijk voor een
situatie waarin veel
nagedacht moet worden.
Helemaal niet O O O O O O O Helemaal wel
op mij
op mij
van toevan toepassing
passing
Nadenken is niet iets dat ik doe voor m’n
plezier.
Helemaal
niet op mij
wel op mij
van toepassing
van toepassing
Ik doe liever iets waarbij weinig
nagedacht hoeft
nagedacht
hoeft
te worden dan iets waarbij mijn
denkvermogen zeker op de proef wordt
gesteld.
op mij
op mij
passing
Ik probeer situaties te vermijden waarin de
de
kans groot is dat ik diep
kans
over iets moet nadenken.
op mij
op mij
passing
Helemaal
niet op mij
wel op mij
van toepassing
van toepassing
Iets langdurig en nauwgezet afwegen
geeft mij voldoening.
Ik denk alleen zoveel als nodig is.
Helemaal
O
niet op mij
van toepassing
Ik denk liever na over kleine dagelijkse dingen Helemaal niet O
dingen dan over lange-termijn zaken.
op mij
van toepassing
Ik hou van taken waarbij weinig nagedacht
Helemaal niet O
nagedacht
hoeft
hoeft
op mij
te worden als ik ze eenmaal geleerd heb.
van toepassing
Het idee dat je op je verstand moet
Helemaal
O
vertrouwen om top te bereiken spreekt mij
niet op mij
van toepassing
aan.
mij aan.
Ik geniet echt van een taak waarbij je met
Helemaal
O
nieuwe oplossingen voor
niet op mij
van toepassing
ppproproblemen
komen.problemen
problemen moetmoet
komen.
moet
komen.
Het leren van nieuwe manieren om te denken Helemaal
O
O O O O O O Helemaal
wel op mij
van
an toepassing
O O O O O O Helemaal wel
op mij
van toepassing
op mij
van toepassing
wel op mij
van toepassing
wel op mij
van toepassing
wel op mij
van toepassing
vind ik niet erg boeiend.
niet op mij
van toepassing
Ik vind het prettig als mijn leven gevuld
is met puzzels die ik moet
oplossen.
oplossen.
Helemaal
niet op mij
wel op mij
van toepassing
van toepassing
Abstract denken is een bezigheid
die mij aanspreekt.
Helemaal
niet op mij
wel op mij
van toepassing
van toepassing
Ik heb liever een taak die intellectueel,
Helemaal
O
moeilijk en belangrijk is, dan een taak die
niet op mij
die
enigszins
belangrijk is, maar waarbij je niet van toepassing
enigszins
belangrijk
veel hoeft na te denken.
Als ik een taak heb voltooid de veel mentale Helemaal niet O
inspanning heeft gevergd ben ik eerder
op mij
opgelucht dan voldaan.
van toepassing
Ik vind het voldoende wanneer iets
Helemaal
O
blijkt te werken: hoe of
niet op mij
waarom het precies werkt
van toepassing
interesseert me niet.
Gewoonlijk denk ik uitgebreid na over
Helemaal
O
zaken, zelfs wanneer ze mij
niet op mij
van toepassing
niet
nietpersoonlijk
persoonlijkaangaan.
aangaan.
wel op mij
van
vantoepassing
op mij
van toepassing
wel op mij
van toepassing
wel op mij
van toepassing
De volgende stellingen bevatten vaak woorden zoals computer of technische
apparaten. Denk hierbij ook aan laptops, smartphones, tablets en andere
technische apparaten.
Als jij een vraag niet begrijpt of geen antwoord kan of wil geven, vul het niet
uit.
Ik wil begrijpen hoe
computer(onderdelen)/Software werken.
Helemaal niet
op mij van
toepassing
O O O O O O O Helemaal wel
op mij van
toepassing
Als er iemand hulp nodig heeft met computers,
probeer ik zo goed mogelijk te helpen.
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Privacy(-instellingen) op de computer of internet
zijn er belangrijk voor mij.
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Gecompliceerde taken met technische
apparaten schrikken mij af.
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Ik heb al eens technische apparaten gebruikt
voor dingen waarvoor ze niet bedoeld zijn, of ze
aangepast.
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Objectiviteit is belangrijk voor mij.
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Ik heb niet het gevoel veel controle over mijn
technische apparaten te hebben.
Helemaal niet
op mij van
toepassing
op mij van
toepassing
In mijn vrije tijd breng ik niet meer tijd door met
computers/technische apparaten dan andere
mensen.
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Wanneer ik nieuwe technische producten koop
is het technische vermogen belangrijker voor mij
dan het uiterlijk.
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Het motiveert mij technische apparaten te
optimaliseren of aan te passen aan mijn
wensen.
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Ik heb al eens projecten/werkstukken van mij
gratis online gezet of zou dit doen.
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Ik denk dat er mensen zijn die mij computerfreak
zouden noemen.
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Het binnenwerk van technische apparaten en/of
het programmeren van software interesseert mij
niet.
Ik vermijd de geavanceerde opties van mijn
technische apparaten.
Helemaal niet
op mij van
toepassing
Helemaal niet
op mij van
toepassing
op mij van
toepassing
op mij van
toepassing
Ik vind het leuk mijn projecten en ideeën met
andere mensen te delen.
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Uitdagende opgaven met de computers
prikkelen mij.
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Ik heb veel kennis over computers
(Hardware/Software).
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Ik probeer dingen zo wetenschappelijk mogelijk
te benaderen.
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Ik ben geïnteresseerd in technische producten
die meervoudig inzetbaar zijn.
Helemaal niet
op mij van
toepassing
op mij van
toepassing
ik investeer veel tijd en moeite dingen met mijn
computerapparaten/Software uit te proberen
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Het is belangrijk dat mensen nadenken over wat
ze op internet zetten en wat niet
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Ik vergaar graag kennis over technische
apparaten (Hardware/Software)
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Ik heb er al vaker computer open gemaakt om te
kijken hoe het er van binnen uitziet
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Het is belangrijk voor mij dat mensen vrij
toegang tot mijn projecten en werken hebben
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Ik hou ervan de computer zo te besturen zoals ik Helemaal niet
het wil
op mij van
toepassing
op mij van
toepassing
Technische apparaten gebruik ik soms anders
dan bedoeld.
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Ik vind het geweldig dat computergebruikers
elkaar helpen bij problemen (Forums, websites).
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Veel instellingen aan technische apparaten vind
ik afschrikkend
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Als ik problemen met technische apparaten heb
moet ik meestal hulp zoeken.
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Een technisch product moet er mooi uitzien.
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Ik hou van computers met veel verschillende
functies
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Ik investeer veel tijd en moeite om dingen met
computerapparaten/software uit te proberen.
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Ik ga bewust om met mijn data en gegevens met
betrekking tot mijn privacy.
Helemaal niet
op mij van
toepassing
op mij van
toepassing
Mijn studie/werk heeft veel met computers en
techniek te maken.
Helemaal niet
op mij van
toepassing
op mij van
toepassing
In hoeverre zijn de onderstaande uitspraken op jou van toepassing?
1. Als ik met computerprogramma’s werk los ik alleen maar taken op, die voor me in deze situatie relevant
zijn.
Trifft auf
mich
überhaupt
nicht zu
O
O
O
O
O
O
O
Trifft auf
mich vollkommen zu
2. Ik stoor me eraan, als ik met een bepaalde computerprogramma een taak niet op de gewenste manier
kan oplossen.
Trifft auf
mich
überhaupt
nicht zu
O
O
O
O
O
O
O
Trifft auf
mich vollkommen zu
3. Tijdens het werken met een computer gebruik ik alleen functies die daadwerkelijk helpen om een taak
op te lossen.
Trifft auf
mich
überhaupt
nicht zu
O
O
O
O
O
O
O
Trifft auf
mich vollkommen zu
4. Ik raak gefrustreerd als ik voor het oplossen van een computer gerelateerde taak meer dan een
programma nodig heb.
Trifft auf
mich
überhaupt
nicht zu
O
O
O
O
O
O
O
Trifft auf
mich vollkommen zu
5. Voor me is het belangrijk dat als ik computerprogramma’s gebruik, ik mijn taak zo knap mogelijk kan
oplossen.
Trifft auf
mich
überhaupt
nicht zu
O
O
O
O
O
O
O
Trifft auf
mich vollkommen zu
6. Voor mij is het belangrijk, dat als ik computerprogramma’s gebruik, ik zo snel mogelijk en op een
makkelijke manier resultaten kan verkrijgen.
Trifft auf
mich
überhaupt
nicht zu
O
O
O
O
O
O
O
Trifft auf
mich vollkommen zu
7. Hoe sneller ik een taak met een computerprogramma kan oplossen, hoe meer ben ik er mee tevreden.
Trifft auf
mich
überhaupt
nicht zu
O
O
O
O
O
O
O
Trifft auf
mich vollkommen zu
Appendix 3. Computer Anxiety Rating Scale (CARS), Original Version
Appendix 4. Computer Anxiety Rating Scale (CARS), German Version
Entscheide für jede der folgenden Aussagen ob du Ihr zustimmst oder nicht und gebrauche dafür die
folgende 5 Punkte Skala. Die Skala reicht von „Ich stimme zu“ bis „Ich stimme nicht zu“. Fülle
eine Zahl von 1-5 neben die Statements ein, die deine Haltung zu dem Statement am besten widerspiegelt.
Ich stimme zu
1
2
3
4
Ich stimme nicht zu
5
1. Ich fühle mich unsicher im Bezug auf meine Fähigkeit einen Computerausdruck zu
interpretieren.
2. Ich freue mich darauf während meiner Arbeit einen Computer zu benutzen.
3. Ich denke nicht, dass ich dazu fähig wäre eine Computerprogrammer Sprache zu erlernen.
4. Die Herausforderung etwas über Computer zu lernen ist sehr aufregend für mich.
5. Ich bin zuversichtlich, dass ich mir auch anspruchsvolle Computerfähigkeiten aneignen kann.
6. Jeder kann lernen einen Computer zu bedienen, wenn er geduldig und motiviert ist.
7. Lernen mit Computern umzugehen ist wie eine neue Fähigkeit zu erlernen – Je mehr du übst,
desto besser wirst du.
8. Ich habe Angst davor, dass ich vom Computer abhängig werde und mein logisches Denken
vernachlässige, wenn ich damit Computer zu viel benutze.
9. Ich bin mir sicher, dass ich mit der Zeit und Übung so gut im Umgang mit Computer werde, wie
ich es im Umgang mit anderen technologischen Geräten bin.
10. Ich fühle mich dazu im Stande, mit den Fortschritten die sich im Computerbereich
Ereignen umgehen zu können.
11. Ich mag es nicht mit Maschinen zu arbeiten die schlauer scheinen als ich.
12. Ich fühle mich nicht wohl dabei, Computer zu benutzen.
13. Ich habe Schwierigkeiten damit, die technischen Aspekte von Computern zu verstehen.
14. Es macht mir Angst daran zu denken, dass ich dafür verantwortlich sein könnt könnte eine
große Datenmenge auf dem Computer zu löschen durch das Drücken der falschen Taste.
15. Ich weigere mich einen Computer zu benutzen weil ich Angst habe Fehler zu machen, die ich
dann nicht korrigieren kann.
16. Du musst ein Genie sein um alle Fähigkeiten des Computers zu verstehen.
17. wenn ich die Möglichkeit bekäme, würde ich gerne mehr über den Computergebrauch lernen.
18. Ich meide Computer, weil sie mir nicht vertraut sind und mich einschüchtern.
19. Ich finde, dass Computer sowohl in Bildungseinrichtungen als auch im Arbeitsfeld
notwendig sind.
Appendix 4. Syntax
DESCRIPTIVES VARIABLES=Gender Age
/STATISTICS=MEAN STDDEV MIN MAX.
FREQUENCIES VARIABLES=Gender
/ORDER=ANALYSIS.
DESCRIPTIVES VARIABLES=exp_Microsoft_Paint exp_Adobe_Photoshop exp_MacPaint
exp_GIMP exp_Paintbrush exp_graphical_programs exp_Microsoft_Word
DESCRIPTIVES VARIABLES=Gex NCS CompAnx AUP_explore AUP_challenge
EXAMINE VARIABLES=Gex NCS CompAnx
/COMPARE VARIABLE
/PLOT=BOXPLOT
/STATISTICS=NONE
/NOTOTAL
/MISSING=LISTWISE.
CORRELATIONS
/VARIABLES=Gex NCS CompAnx AUP_explore AUP_challenge
/PRINT=TWOTAIL NOSIG
/MISSING=PAIRWISE.
EXAMINE VARIABLES=AUP_explore AUP_challenge
/COMPARE VARIABLE
/PLOT=BOXPLOT
/STATISTICS=NONE
/NOTOTAL
/MISSING=LISTWISE.

Exploring People`s resistance to the Active User Paradox including

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