Handbook of Personalized Learning
1st Edition
Published on 26. November 2025
Book
Paperback/Softback
460 pages
978-1-032-71944-3 (ISBN)
Description
The Handbook of Personalized Learning offers a theoretically grounded conceptualization for the development and implementation of personalizing learning. This comprehensive volume addresses personalized learning's roots in educational, cognitive, and social psychological studies of learning as well as in practice. Positioned to shape the future of personalized learning, this handbook documents past innovations achieved in educational technology research and development; considers how advancements in learning analytics and machine learning have influenced policy and implementation; and showcases current and future applications of personalized learning in diverse K-12 classrooms, higher education, and informal educational settings. The book's varied, rigorous contributions are informed by an overarching model of personalized learning that centers the assets individuals bring to learning opportunities (including their prior knowledge, interests, self-beliefs, autonomy, and identity) and whose responsive designs build on those assets to improve learning and attainment. Researchers, developers, teaching faculty, and graduate students across educational psychology, educational technology, the learning sciences, learning analytics, human-computer interaction, and beyond will come away with substantive foundations and cutting-edge exemplars of the ways in which designs can be personalized to promote learners' experiences in educational settings.
Chapter 25 of this book is freely available as a downloadable Open Access PDF at http://www.taylorfrancis.com under a Creative Commons Attribution-Non Commercial-No Derivatives (CC BY-NC-ND) 4.0 license.
Chapter 25 of this book is freely available as a downloadable Open Access PDF at http://www.taylorfrancis.com under a Creative Commons Attribution-Non Commercial-No Derivatives (CC BY-NC-ND) 4.0 license.
Reviews / Votes
"This comprehensive guide offers critical insight for those designing and implementing educational technologies that support personalized learning. Drawing from cognitive, motivational, and sociocultural research, it presents clear frameworks for integrating learner characteristics, such as interests, prior knowledge, and self-beliefs into adaptive systems. The content bridges theory and application, illustrating how data-informed personalization can shape responsive, inclusive, and effective learning experiences across diverse educational settings. It is a vital resource for anyone developing technology that seeks to align learning design with the individuality of each learner."- Helen Crompton, Executive Director of the Research Institute for Digital Innovation in Learning at ODUGlobal, Professor of Instructional Technology, and Director of the Virtual Reality Lab at Old Dominion University, USA
"The Handbook of Personalized Learning is the compass education has been waiting for-deeply rooted in theory, expansive in its practical vision, and unapologetically forward-looking. It doesn't just trace the arc of personalized learning-it bends it toward equity, relevance, and innovation. With insights from some of the sharpest minds in the field, this book offers a blueprint for designing learning environments where every learner's individuality is the starting point, not an afterthought. It is a must-read for anyone serious about making learning more human in an age of intelligent systems."
- James D. Basham, Professor in the Department of Special Education at the University of Kansas, USA
More details
Series
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Professional and scholarly
Postgraduate and Professional Reference
Illustrations
73 s/w Abbildungen, 46 s/w Photographien bzw. Rasterbilder, 27 s/w Zeichnungen, 21 s/w Tabellen
21 Tables, black and white; 27 Line drawings, black and white; 46 Halftones, black and white; 73 Illustrations, black and white
Dimensions
Height: 254 mm
Width: 178 mm
Thickness: 26 mm
Weight
906 gr
ISBN-13
978-1-032-71944-3 (9781032719443)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Matthew L. Bernacki | Candace Walkington | Alyssa Emery
Handbook of Personalized Learning
E-Book
11/2025
Routledge
€158.99
Available for download
Matthew L. Bernacki | Candace Walkington | Alyssa Emery
Handbook of Personalized Learning
E-Book
11/2025
Routledge
€158.99
Available for download
Matthew L. Bernacki | Candace Walkington | Alyssa Emery
Handbook of Personalized Learning
Book
11/2025
1st Edition
Routledge
€331.90
Shipment within 10-20 days
Persons
Matthew L. Bernacki is Associate Professor of Learning Sciences and Psychological Studies and Kinnard White Endowed Scholar in the School of Education at the University of North Carolina at Chapel Hill, USA.
Candace Walkington is Professor of Mathematics Education and the Annette and Harold Simmons Centennial Chair in the Department of Teaching and Learning at Southern Methodist University, USA.
Alyssa Emery is Assistant Professor of Learning Sciences in the School of Education at Iowa State University, USA.
Ling Zhang is Assistant Professor of Special Education in the College of Education at the University of Wyoming, USA.
Candace Walkington is Professor of Mathematics Education and the Annette and Harold Simmons Centennial Chair in the Department of Teaching and Learning at Southern Methodist University, USA.
Alyssa Emery is Assistant Professor of Learning Sciences in the School of Education at Iowa State University, USA.
Ling Zhang is Assistant Professor of Special Education in the College of Education at the University of Wyoming, USA.
Content
Section 1. An Introduction to Personalized Learning 1. Trends in Personalized Learning 2. A History & Taxonomy of Personalized Learning 3. An Extensible Model of Personalized Learning Section 2. Exemplary Models of Personalized and Adaptive Learning 4. An Exemplar: Personalized Learning from the Perspective of Intelligent Tutoring Systems 5. An Exemplar: Personalized Learning in Educational Games Using Stealth Assessment Section 3. Psychological Theories of Learning that Can Inform Personalized Learning Design 6. Adapting to Prior and Developing Knowledge 7. Personalizing Learning to Promote Interest 8. Personalizing Learning to Promote Relevance 9. Personalizing with Choices to Promote Autonomy: A Self-Determination Perspective on Personalized Learning Design 10. Personalizing to Individual Differences: Promoting Inclusive and Equitable Opportunities for Learning Section 4. Instructional Designs for Personalized Learning 11. Culturally Responsive Personalized Learning 12. Leveraging Digital Curation for Personalized Learning 13. Project-Based Instruction as Personalized Learning 14. Personalized Learning in the Age of Generative Artificial Intelligence: Opportunities and Challenges Section 5. PL in Academic Subjects 15. Personalized Learning in Mathematics 16. Personalized Learning in English Language Arts: Reading Comprehension 17. Personalized Learning in Social Studies 18. Theoretical, Empirical, and Illustrative Considerations of Personalized Learning within Computer Science Education Section 6. Personalization For Learners, Teachers, and Communities 19. Personalized Learning for Early Learners 20. Applying Self-Determination Theory to the Effective Implementation of Personalized Learning in Online Higher Education 21. Holistic Individualized Coaching: A Personalized Learning Approach to Support Teacher Learning 22. Anishinaabe Indigenous & Extensible Models of (Inter-Species)-Personalized Learning: Towards a Holistic Revision Section 7. Implementing Personalization: Policy, Technology, and Contextual Considerations 23. Understanding Personalization and Individualization from Education Policy Perspectives: Towards an Integrated School-Wide Implementation System 24. Teacher Perspectives on Implementing Personalized Learning across Contexts 25. Design and Implementation Factors for Digital Personalized Learning in Low- and Middle-Income Countries 26. Asset-based Personalized Learning