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Abstract

Adaptive learning technologies provide an environment that intelligently adjusts to a ­learner’s needs by presenting suitable information, instructional materials, feedback and recommendations based on one’s unique individual characteristics and situation. This chapter first focuses on the concept of adaptivity based on four types of learner differences that can be used by adaptive technologies: learning styles, cognitive abilities, affective states and the current learning context/situation. In order to provide adaptivity, the characteristics of learners need to be known first. Therefore, this chapter discusses methods for identifying learners’ individual differences as well as how the information about these individual ­differences can be used to provide learners with adaptive learning experiences. Furthermore, the chapter demonstrates how adaptivity can be provided in different settings, focusing on both desktop-based learning and mobile/pervasive/ubiquitous learning. Finally, open issues in adaptive technologies are discussed and future research directions are identified.

Keywords

Affective states Cognitive abilities Context Context modeling Learning styles Student modeling 

Notes

Acknowledgements

The authors also acknowledge the support of NSERC, iCORE, Xerox, and the research-related gift funding by Mr. A. Markin.

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.School of Computing and Information SystemsAthabasca UniversityEdmontonCanada
  2. 2.School of Computing and Information SystemsAthabasca UniversityAthabascaCanada

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