Mobile and ubiquitous learning technologies
Transcription
Mobile and ubiquitous learning technologies
Mobile and ubiquitous learning technologies prof. dr. marcus specht Open Universiteit Nederland, Centre of Learning Sciences and Technologies CELSTEC celstec.org, http://portal.ou.nl/en/web/ topic-mobile-learning [email protected], social media: marcuspecht 1 #FTI2012 #Context #CELSTEC #OpenUniversiteit #researchGroup TEL 2 Some Facts: - 20.000 Students - 60 Mio Budget - 15 Study Centers CELSTEC - 120 fte, 7 Mio budget Research Lines and topics #1 Mobile and ubiquitous learning content Ubiquitous access to learning support and distributed multi-format learning content. – Mobile Video and Audio Content (Youtube EDU, iTunes U), Cloudbased learning content, Mobile data collection and aggregation, eBooks and tablet content. #2 Orchestration of seamless learning support Instructional design of nomadic and seamless learning support. – Ubiquitous LMS access, Mixed Reality Games, Excursions and Field Trip systems, Mobile Augmented Reality, Mobile Learning Games, Object and location-based service access. #3 Situated learning experiences Connect the Learning and the real World, context-aware learning systems, sensor-based learning support. – Experience sampling apps, Sensor-based learning apps, Situated and ambient displays, Context-aware social media, Tangible and smartobjects for learning Mobile Learning Applications Domains • eHealth and healthcare EMURGENCY: performance support and notification system, Handover procedures, Reference apps for daily practice • Law and Management education OpenScout, OUNL iPad pilots, UNHCR mobile simulated games • Architecture and creative industries MACE location-based content and social media, Cloud-based cooperation methods in design and architecture • Cultural Heritage Mixed reality field trips with Cultural Sciences • Logistics SALOMO: Situation Awareness and Mobile data collection • Language learning ELENA, PhD projects • Teacher education and networking mobile social networking apps b a L tion n i n r a Le a v o n g In #mobilelearning #ContextAwareComputing #challenges 7 ontological challenge: what is context and how can we conceptualize it to better understand learning in context ? context is multi-displinary body network sensors, rooms intelligent carpets, wall colour, or gesture tracking, building , architects already create completely new facades for buildings, public places and city planning new artefacts will enable dynamic routing and highlighting of space Sybren A. Stüvel, “Colours and bricks” via Flickr, Creative Commons Attribution. context is always ... context is dynamic ... context is social ... context is connecting ... engineering challenge: what are the opportunities for technology to enhance learning in context ? #sensor technology can record data in a scalable way. http://quantifiedself.com/ #cloud technology can support seamless learning trajectories. d i s a p p e a ri n g Wong, L.-H., & Looi, C.-K. (2011). What Seams Do We Remove in Mobile Assisted Seamless Learning? A Critical Review of the Literature. Computers & Education, 57(4), 2364-2381. Elsevier Ltd. doi:10.1016/ j.compedu.2011.06.007 #AR technology can augment your perception of a context ... http://www.designbynotion.com/metamirror-next-generation-tv/ #display technology can create feedback loops ... Goetz, T. (2011). Harnessing the Power of Feedback Loops | Magazine. wired.com. Retrieved August 22, 2011, from http://www.wired.com/magazine/ 2011/06/ff_feedbackloop/5/ #display tech. can support awareness and reflection. Bachour, K., Kaplan, F., & Dillenbourg, P. (2008). Reflect : An Interactive Table for Regulating Face-to-Face Collaborative Learning. Technology, 39-48. Retrieved from http://dx.doi.org/ 10.1007/978-3-540-87605-2_5 #visualisation and LA can support personal sense making. Heer, J., Shneiderman, B. (2012). Interactive Dynamics for Visual Analysis. Communications of the ACM. Vol 55. No 04. pp. 45-54. Lo c a t i o n ID Tim e ati . Rel on Env # the plan: how to model and design this: Ambient Information CHannEls AICHE Ti m n o i at Artefact Lo c a t i o n Tim e Ti me ID ID Artefact Re lat v. User n E n v. Channel Lo c at i o n ion En n o i t a l Re ID e L o c E . v n Re latio Ti ID me Relation ati c o L on Env . Aggregation Sensor Sensor Sensor AICHE Processes Sensor Sensor Re Re Tim e Artefact Lo c a t i o n Re Env Lo c a t i o n Tim e Channel on i t la ID Tim e Env ID ID User on i t la . . Env . on i t la Lo c a t i o n Enrichment Ti Lo c AICHE Processes ID me Relation ation Env . Aggregation Sensor Sensor Sensor Sensor Sensor e Ti m Rel on Artefact Env n Lo c a t i o n l on Re e ati Tim Lo c at i o User ati Ti m e ID Channel Loc on i t a ID Re l atio n E n v. E n v. . ID Channel Re Tim e Re Tim e Env lat ion Env Artefact ID Lo c a t i o n Tim e ion ID ID User lat . Env Lo c a t i o n ion . lat . Re Synchronisation Lo c a t i o n Enrichment Ti Lo c AICHE Processes ID me Relation ation Env . Aggregation Sensor Sensor Sensor Sensor Sensor n Re l atio e on Rel on ID e ati Lo c at i o User Tim Artefact Env n Lo c a t i o n l Ti m Ti m e Re Channel Loc ati ID Artefact E n v. . ID E n v . Loc n ID Re l atio e Ti m n Lo c a t i o n on E n v. on on l Rel ati ati Re E n v. e ati Tim Lo c at i o User Loc Ti m n Channel e ID ID on i t a Re latio Channel Ti m e E n v. on i t a E n v. ID Channel Tim e Re Tim e Env lat ion Env Artefact ID Lo c a t i o n Tim e ion ID ID User lat . Env . Re ion . lat Lo c a t i o n Framing Re Synchronisation Lo c a t i o n Enrichment Ti Lo c AICHE Processes ID me Relation ation Env . Aggregation Sensor Sensor Sensor Sensor Sensor Loc on n ID Re l atio n Ti m on l e Rel ati Tim Artefact Env n Lo c a t i o n on Lo c at i o User ID ati Ti m E n v. e Channel Loc Re ID on Re latio Channel e E n v. . ID Framing e Rel on ID e ati Lo c at i o User Tim Artefact Env n Lo c a t i o n l Re Ti m on Ti m ati on Channel Loc ati ID Re l atio n E n v. e E n v. . ID Channel Re Env Tim e ion lat ion Env Artefact ID Lo c a t i o n Tim e lat ID ID User Tim e Re Env Lo c a t i o n ion . lat . Re Synchronisation . Lo c a t i o n AICHE brings together context-aware computing, semantic-web technologies, instructional design for adaptive and personal learning, HCI aspects as tangible computing and IOThings. ati Ti m e E n v. ati Enrichment Ti Lo c AICHE Processes ID me Relation ation Env . Aggregation Sensor Sensor Sensor Sensor Sensor #research #Context #CELSTEC #OpenUniversiteit 28 creation and management of iTunes U channel and media workflows for the OU o i d u a / o m e d i v e l i b o t n e t n co 29 Youtube Channel of the OU 30 Content Bundles via iBooks e s k Boo 31 Mooble LMS s s cce a S LM Glahn, C., & Specht, M. (2010). Embedding Moodle into Ubiquitous Computing Environments. In M. Montebello, et al. (Eds.), 9th World Conference on Mobile and Contextual Learning. October, 19-22, 2010,Valletta, Malta. http://hdl.handle.net/1820/2729 Blackboard Mobile Learn c a l B d r a kbo e l i b o M , e r u t c u r t s , a ) r f R n Q i , r C o F s n N ( e se s l i g b a o T , m r e n i w d l i po u b , n o i t a loc h"p://www.plugwise.com/ Experiment 2 , n o i t a g e r g g . . a . , a t s a e i d r o r t o a r s e n d e e s f , a t a d a t e m Experiment 3 o s r pe d n i nal s r o icat n g i s e d l a n o i t c u g r n t i s m in a r f t s e b r o f Context Indicators a t n e i b m s y a l p s i t i s d n a d d e t a u Experiment 2 s r o t a c i d n i t x e t n o c E+ IL Reflection Amplifiers mobile RA d n a g n i l p m a s n e o c i t n c e i e l r l e o p c a ex t a d e l i b mo EyeStop s s e n e r a w a r s fo d e t a u t i y a l p s i d s Hello.Wall Flower Lamp Digital Retail Ambient Umbrella UbiGreen Power Aware Cord Orb BBC Nuage Vert ARLearn framework http://code.google.com/p/arlearn/ • Augmented Reality Games, • Excursions, • Mixed Reality Games, • Mobile Games and Simulations. e c r u o s n ope work e m g fra n i r o h t Au p p A e l i b Mo n r a e L t e Stre ! ! 42 www.openU.nl, celstec.org, marcuspecht.de