Designing Adaptive and Personalized Learning Environments provides a theoretically-based yet practical guide to systematic design processes for learning environments that provide automatic customization of learning and instruction.
Designing Adaptive and Personalized Learning Environments provides a theoretically-based yet practical guide to systematic design processes for learning environments that provide automatic customization of learning and instruction.
Kinshuk is Associate Dean of Faculty of Science and Technology and Full Professor in the School of Computing and Information Systems at Athabasca University, Canada. He also holds the NSERC/CNRL/Xerox/McGraw Hill Industrial Research Chair for Adaptivity and Personalization in Informatics. He is founding chair of IEEE Technical Committee on Learning Technologies, and founding editor of the Journal of Educational Technology and Society and the Smart Learning Environments journal.
Inhaltsangabe
Acknowledgements Section 1: Introduction and Overview Chapter 1: Defining Adaptivity and Personalization Chapter 2: Adaptivity and Personalization in Life-Long Learning Chapter 3: Contexts Section 2: Theoretical Perspectives with Example Applications Chapter 4: Cognitive Profiling Chapter 5: Content-Based Adaptivity and Personalization Chapter 6: Adaptivity and Personalization in Exploration-Based Learning Chapter 7: Adaptivity and Personalization in Mobile and Ubiquitous Settings Section 3: Practical Perspectives with Example Applications Chapter 8: Implementation Process of Adaptive and Personalized Learning Environments Chapter 9: Adaptivity and Personalization of Learning in Various Contexts Chapter 10: Reusability in Adaptive and Personalized Learning Section 4: Validation and Future Trends Chapter 11: Evaluation of Adaptive and Personalized Systems Chapter 12: Future Development and Research Issues Index
Acknowledgements Section 1: Introduction and Overview Chapter 1: Defining Adaptivity and Personalization Chapter 2: Adaptivity and Personalization in Life-Long Learning Chapter 3: Contexts Section 2: Theoretical Perspectives with Example Applications Chapter 4: Cognitive Profiling Chapter 5: Content-Based Adaptivity and Personalization Chapter 6: Adaptivity and Personalization in Exploration-Based Learning Chapter 7: Adaptivity and Personalization in Mobile and Ubiquitous Settings Section 3: Practical Perspectives with Example Applications Chapter 8: Implementation Process of Adaptive and Personalized Learning Environments Chapter 9: Adaptivity and Personalization of Learning in Various Contexts Chapter 10: Reusability in Adaptive and Personalized Learning Section 4: Validation and Future Trends Chapter 11: Evaluation of Adaptive and Personalized Systems Chapter 12: Future Development and Research Issues Index
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