A Multiple Response Approach for Adaptive Learning Service with Context-Based Multimedia Contents

Learners can benefit more from the emerging ubiquitous computing technology in more learning scenarios beyond traditional computer-based e-learning system. But due to the great diversity of device specification, learning contents, and mobile context existing today, learners may have a poor learning experience in the ubiquitous computing technology-enhanced learning (u-learning) environment. This paper proposes a multiple response approach for adaptive learning service with context-based multimedia contents, which recommends preferred media for learners according to the u-learning environment. Based on six learning statuses from SCORM, five learning responses of learning objects are used to reward or penalize the preferred media according to the learning context. In the evaluation experiment, the accessed object, time, location and mobile device are mainly used as context data. With the comparison between the controlled group and non-controlled group, the results show that the proposed method can improve the utilization rate of learning objects which implies that the learners are more interested in these recommended media. The results also show that the learning experience is improved.

[1]  Miguel-Angel Sicilia,et al.  On the Concepts of Usability and Reusability of Learning Objects , 2003 .

[2]  Owen Conlan,et al.  Metadata Driven Approaches to Facilitate Adaptivity in Personalized eLearning Systems , 2003 .

[3]  Tomoko Kojiri,et al.  Device-independent Learning Contents Management in Ubiquitous Learning Environment , 2007 .

[4]  Ben Shneiderman,et al.  Readings in information visualization - using vision to think , 1999 .

[5]  Stephen J. H. Yang,et al.  Applying Content Adaptation Technique to Enhance Mobile Learning on Blackboard Learning System , 2007, Seventh IEEE International Conference on Advanced Learning Technologies (ICALT 2007).

[6]  Panagiotis Germanakos,et al.  Adaptation and Personalization of Web-Based Multimedia Content , 2006 .

[7]  Toshio Okamoto,et al.  Adaptive multimedia content delivery for context-aware u-learning , 2011, Int. J. Mob. Learn. Organisation.

[8]  V. Shute,et al.  Adaptive E-Learning , 2003, Educational Psychologist.

[9]  Tatsuya Yamazaki,et al.  The Ubiquitous Home , 2007 .

[10]  Joseph J. Corn Yesterday's Tomorrows , 1984 .

[11]  Mike Sharples,et al.  Big Issues in Mobile Learning , 2005 .

[12]  Paul Dourish,et al.  Yesterday’s tomorrows: notes on ubiquitous computing’s dominant vision , 2007, Personal and Ubiquitous Computing.

[13]  Hong Chen,et al.  Open Learning: A Framework for Sharable Learning Activities , 2010, ICWL.

[14]  Qun Jin,et al.  Dynamic Navigation for Personalized Learning Activities Based on Gradual Adaption Recommendation Model , 2010, ICWL.

[15]  Mohamed Ally,et al.  Mobile Learning: Transforming the Delivery of Education and Training , 2009 .

[16]  Martin Oliver,et al.  Maintaining, Changing and Crossing Contexts: An Activity Theoretic Reinterpretation of Mobile Learning. , 2008 .

[17]  R Barthel,et al.  Standardization in e-Learning. The "Sharable Content Object Reference Model (SCORM)” , 2004 .

[18]  Anastasios A. Economides Adaptive Mobile Learning , 2006 .

[19]  Anastasios A. Economides Multiple response learning automata , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[20]  Patrick E. Parrish,et al.  The trouble with learning objects , 2004 .

[21]  Ming-Syan Chen,et al.  Versatile Transcoding Proxy for Internet Content Adaptation , 2008, IEEE Transactions on Multimedia.

[22]  Matt Jones,et al.  Mobile Interaction Design , 2006 .

[23]  Qun Jin,et al.  Flowable Services: A Human-Centric Framework toward Service Assurance , 2011, 2011 Tenth International Symposium on Autonomous Decentralized Systems.