Designing Adaptive and Personalized Learning Environments

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. The book consists of four main sections: In "Introduction and Overview," the concepts of adaptivity and personalization are introduced and explored in detail. In "Theoretical Perspectives with Example Applications," various theoretical concepts underlying adaptive and personalized learning are discussed, including cognitive profiling, content-based adaptivity, exploration-based adaptivity, and mobile and ubiquitous settings. In "Practical Perspectives with Example Applications," the implementation process for adaptive and personalized learning environments is described, followed by application in various contexts. In "Validation and Future Trends," various evaluation techniques for validating the efficiency and efficacy of adaptive and personalized learning systems are discussed. This final section concludes with a discussion of emerging trends in adaptive and personalized learning research. Based on cutting-edge research, Designing Adaptive and Personalized Learning Environments is appropriate as a primary textbook for both undergraduate and graduate courses focused on the design of learning systems, and as a secondary textbook for a variety of courses in programs such as educational technology, instructional design, learning sciences, digital literacy, computer based systems, and STEM content fields.

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.

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