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IJIET 2013 Vol.3(5): 529-535 ISSN: 2010-3689
DOI: 10.7763/IJIET.2013.V3.330

Location-Based Learning Management System for Adaptive Mobile Learning

Frederick Ako-Nai and Qing Tan

Abstract—E-learning and distance learning are all forms of learning that take place outside of a traditional learning environment and can be alternatives for learners who are not able to study in a traditional environment for various reasons. With advancement in technologies and increased use of smart phone, mobile learning has gained popularity as another form of learning and has enabled learners to learn anywhere and anytime. Ubiquitous learning takes mobile learning to another level by providing contents that are context and location aware. There is therefore the need to provide mobile devices with the right learning contents for the right users. The right learning contents should be adaptive to the learner’s location, as well as learning style and device etc. To be able to implement the learning, learning management systems play the important role in creating, managing, and delivering the learning contents. In this paper, a location-based Learning Management System for adaptive and personalized mobile learning is presented. The systems makes use of 5R Adaptation Framework for Location based Mobile learning, the location-based dynamic grouping algorithm, and concepts of the IMS Learning Design model to produce a location-based adaptive mobile learning setting.

Index Terms—Adaptive and personalized learning, location and context awareness, learning management system, mobile learning.

The authors are with the School of Computing and Information Systems, Athabasca University, Athabasca, AB T9S 3A3 Canada (e-mail: fako-nai@outlook.com, qingt@athabascau.ca).


Cite:Frederick Ako-Nai and Qing Tan, "Location-Based Learning Management System for Adaptive Mobile Learning," International Journal of Information and Education Technology vol. 3, no. 5, pp. 529-535, 2013.

General Information

  • ISSN: 2010-3689 (Online)
  • Abbreviated Title: Int. J. Inf. Educ. Technol.
  • Frequency: Monthly
  • DOI: 10.18178/IJIET
  • Editor-in-Chief: Prof. Dr. Steve Thatcher
  • Executive Editor: Ms. Nancy Y. Liu
  • Abstracting/ Indexing: Scopus (CiteScore 2022: 2.0), INSPEC (IET), UGC-CARE List (India), CNKI, EBSCO, Google Scholar
  • E-mail: ijiet@ejournal.net


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