Home   >   CSC-OpenAccess Library   >    Manuscript Information
Full Text Available

This is an Open Access publication published under CSC-OpenAccess Policy.
Adaptive Approaches to Context Aware Mobile Learning Applications
Uday Bhaskar Nagella, P. Govindarajulu
Pages - 15 - 26     |    Revised - 15-4-2008     |    Published - 30-4-2008
Volume - 2   Issue - 2    |    Publication Date - April 2008  Table of Contents
adaptation, adaptive learning, context, learning activity, learner model, learning automata
Learning has gone through major changes from its inception in the human race. Among all such major changes mobile learning is the latest to happen with the advent of mobile learning technologies that have the potential to revolutionize distance education by bringing the concept of anytime and anywhere to reality. From the learner’s perceptive, mobile learning is “any sort of leaning that happens when the learner is not at a fixed, pre-determined location or learning that happens when the learner takes advantage of learning opportunities offered by mobile technologies”. Research in context aware mobile learning has concentrated on how to adapt applications to context. This paper reviews and discusses few mobile learning systems the approach in implementing context awareness and adaptation
CITED BY (19)  
1 Loto, m., & durn, e. B. (2015). Diseo de una aplicacin mvil personalizada de apoyo al aprendizaje de redes de computadoras. In x congreso sobre tecnologa en educacin & educacin en tecnologa (te & et)(corrientes, 2015).
2 Castro, g. G., domnguez, e. L., velasquez, y. H., & matla, y. R. Sistema de aprendizaje mvil consciente de contexto.
3 Koondhar, m. Y., rind, m. M., chandio, f. H., & shah, a. (2015). Pervasive learning environment with emerging technologies and learning transformation. In international multi-topic conference.
4 Karadimce, a., & davcev, d. (2014, october). Collaborative cloud service model for delivering multimedia content in mcloud. In collaborative computing: networking, applications and worksharing (collaboratecom), 2014 international conference on (pp. 469-474). Ieee.
5 Kalinic, z., arsovski, s., arsovski, z., & rankovic, v. The effectiveness and students perception of an adaptive mobile learning system based on personalized content and mobile web. Stanislaw juszczyk, 43.
6 Mehigan, t. J. (2013). Automatic detection of learner-style for adaptive elearning.
7 Sun, g. (2013). Teamwork as a service: design of a cloud-based system for enhancing teamwork performance in mobile learning.
8 Haghshenas, m., & jeddi, k. Y. (2013). Using mobile devices to improve learning technologies. Ijitr, 1(6), 519-523.
9 Gmez ardila, s. E. (2013). Learning design implementation in context-aware and adaptive mobile learning.
10 Harchay, a., cheniti-belcadhi, l., & braham, r. (2012, june). Towards a formal description of mobile personalized assessment. In communications and information technology (iccit), 2012 international conference on (pp. 270-275). Ieee.
11 Anwar, r. W., sherimon, p. C., & vinu, p. V. A semantic web approach for searching and accessing information in blended learning systems.
12 Harchay, a., cheniti-belcadhi, l., & braham, r. (2012, june). A model driven infrastructure for context-awareness mobile assessment personalization. In trust, security and privacy in computing and communications (trustcom), 2012 ieee 11th international conference on (pp. 1676-1683). Ieee.
13 Vinu, p. V., sherimon, p. C., & krishnan, r. (2011). Towards pervasive mobile learningthe vision of 21st century. Procedia-social and behavioral sciences, 15, 3067-3073.
14 Kantore, a. (2011). User-interface evaluation metrics for a typical m-learning application. The school of information communication and technology. Nelson mandela metropolitan university.[accessed march 2013]. Available from: http://books. Google. Com. Br/books.
15 Basoglu, n., & zdogan, k. (2011). Exploring the major determinants of mobile learning adoption.bogazici university training journal, 28(1).
16 Liu, c., & h eljueidi, m. A. (2011). Towards an analysis framework to facilitate informal mobile colleborative learning with context awareness. Mobile, 19.
17 P.V. Vinu, P.C. Sherimon and Reshmy Krishnan, Towards Pervasive Mobile Learning The Vision Of 21st Century, in Proceedings Procedia - Social and Behavioral Sciences Volume 15, 3rd World Conference on Educational Sciences 2011, pp. 30673073.
18 P. C. Sherimon, P. V. Vinu and R. Krishnan, Enhancing The Learning Experience In Blended Learning Systems: A Semantic Approach, in Proceedings of the 2011 International Conference on Communication, Computing & Security, New York, USA, 2011.
19 X. Zhao, Adaptive Content Delivery Based on Contextual and Situational Model, Thesis For The Degree of Doctor of Philosophy in Engineering, The Graduate School of Information Systems, The University of Electro-Communications Tokyo, Japan, September 2010.
1 Google Scholar
2 Academic Journals Database
3 ScientificCommons
4 Academic Index
5 CiteSeerX
6 refSeek
8 Socol@r
9 ResearchGATE
10 Libsearch
11 Bielefeld Academic Search Engine (BASE)
12 Scribd
13 WorldCat
14 SlideShare
16 PdfSR
17 Chinese Directory Of Open Access
1 Derntl, M. and Hummel, K. (2005) Modelling context-aware e-learning scenarios. Pervasive computing and communications workshop.
2 Chan, T., Sharples, M., Vavoula, G. and Lonsdale, P. (2004) Educational Metadata for mobile learning, International Workshop on Wireless and Mobile Technologies in Education.
3 Malek, J., Laroussi, M. and Derycke, A. (2006) A Multi-Layer Ubiquitous Middleware for Bijective Adaptation between Context and Activity in a Mobile and Collaborative learning. ICSNC 2006.
4 Lavoie, M. (2006) Mlearning: Identifying Design Recommendations for a context-aware mobile learning system. IADIS International Conference Mobile Learning.
5 Anu Jappinen, Mikko Ahonen, Teija Vainio, Erika Tanhua -Piiroinen.(2004). Adaptive mobile learning systems the essential issues from the design perspective. In the proceedings of MLearn 2004.
6 Antti Syvanen, Russell Beale, Mike Sharples, Mikko Ahonen and Peter Lonsdale. (2005) Supporting Pervasive Learning environments: Adaptibility and Context Awareness in Mobile Learning, In the Proceedings of the 2005 IEEE International Workshop on Wireless and Mobile Technologies in Education (WMTE05).
7 Jane Yau and Mike Joy (2007). Architecture of a Context-aware and Adaptive Learning Schedule for Learning Java. ICALT ,2007.
8 R. Beale and P. Lonsdale, Mobile Context Aware Systems: the intelligence to support tasks and effectively utilize resources, Mobile HCI, 2004.
9 Y. Cui and S. Bull, Context and learner modeling for the mobile foreign language learner, Science Direct, System 33, pp.353-367, 2005.
10 Estefania Martin, Nuria Andueza, Rosa M. Carro (2006), Architecture of a System for Context-based Adaptation in M-Learning, In the Proceedings of the Sixth International Conference on Adavanced Learning Technologies (ICALT06).
11 Yuan-Kai Wang (2004), Context Awareness and Adaptation in Mobile Learning, In the Proceedings of the second IEEE International Workshop on Wireless and Mobile Technologies in Education (WMTE04).
12 Economides, A.A.(2006), Adaptive Mobile Learning, Proceedings WMUTE 4th International Workshop on Wireless, Mobile and Ubiquitous Technologies in Education, 2006.
13 Economides, A.A., Multiple response learning automata, IEEE Transactions on Systems, Man and Cybernetics, Vol. 26, No 1, pp.153-156, February 1996.
14 Yu Dan, Chen XinMeng, Using Bayesian Networks to Implement Adaptivity in Mobile Learning, Proceedings of the second International Conference on Semantics, Knowledge, and Grid(SKG06).
15 Kinshuk and T. Lin, Application of Learning Styles Adaptivity in Mobile Learning Environments, in Third Pan-Commonwealth Forum on Open Learning, Dunedin, New Zealand, 2004.
16 R. Felder and L. Silverman, Learning and Teaching Styles, Journal of Engineering Education, vol.78, no.7, 1988,pp.674-681.
17 P. Garcia, A. Amandi, S. Schiaffino and M. Campo, Using Bayesian Networks to Detect Students Learning Styles in a Web-based Education System, in Proc of ASAI, Rosario, 2005, pp. 115-126.
18 Shanghua Sun, Mike Joy & Nathan Griffiths, To Support Adaptivity in Agent-Based Learning System The Use of Learning Objects and Learning Style, Proceedings of the fifth IEEE International Conference on Advanced Learning Technologies (ICALT05).
19 S. Sun, M. Joy, and N. Griffiths, The use of learning objects and learning styles in a multiagent education system, Proc. of ED-MEDIA 2005.
20 J. Kolari, T. Laakko, T. Hiltunen, V. Ikonen, M. Kulju, R. Suihkonen, S. Toivonen and T. Virtanen, Context-aware services for mobile users technology and experiences, VTT publications 539, 2004.
Mr. Uday Bhaskar Nagella
Sri Venkateswara University - India
Mr. P. Govindarajulu
Sri Venkateswara University - India