Personalized Learning
Routledge (Verlag)
978-1-032-58186-6 (ISBN)
Personalized learning emphasizes student-centred learning that addresses individual learning strengths, needs, skills, and interests, and allows flexibility in the learning mode, process, time and space, where students can take ownership of their learning. It has been practiced in educational institutions at both K-12 and higher education level and, as evident from several successful cases, is an enabler of personalized learning. Educational technology incorporated with other forms of innovative pedagogical practices, such as blended learning, makes personalized learning a reality to achieve its aims effectively and efficiently. This book begins with a critical review on the features and trends of personalized learning. This is followed by a number of case studies on personalized learning practices with promising results. The latest research findings on the approaches, methods and strategies on design and implementation of personalized learning are then reported. Lastly, the prospects of personalized learning are discussed. All these provide some useful references for researchers and practitioners in the field in conceptualizing and deploying personalized learning.
Personalized Learning will be a key resource for academics, researchers, and advanced students of education, instructional design and technology, educational research, educational technology, research methods, STEM Education, information and communications technology, and curriculum and instruction. The chapters included in this book were originally published as a special issue of Interactive Learning Environments.
Simon K.S. Cheung is currently the Director of IT in Hong Kong Metropolitan University. He is active in research, with over 200 publications in the form of books, book chapters, journal articles and conference papers in two distinct areas, namely, innovation and technology in education, and software and systems engineering. Fu Lee Wang is currently Professor and the Dean of Science and Technology in Hong Kong Metropolitan University. He has widely engaged in research in areas pertaining to applied algorithm, educational technology, information retrieval and machine learning, with over 200 articles in refereed journals and conference proceedings. Lam For Kwok is currently Governor in HKCT Institute of Higher Education. Prior to this, he was an Associate Professor in the Department of Computer Science in City University of Hong Kong. His research interests include information security and management, computers in education and smart learning environment. Petra Poulová is currently Associate Professor and the Vice Dean for Development and International Affair of the Faculty of Informatics and Management in University of Hradec Králové. Her research interests include IT in teaching and learning, learning and teaching styles, social networking, and database and information systems.
1. Toward Good Practices of Personalized Learning 2. Features and Trends of Personalised Learning: A Review of Journal Publications from 2001 to 2018 3. Personalized Learning in Microscopic Method for Identification of Herbal Medicines 4. Use of Fitness Trackers in a Blended Learning Model to Personalize Fitness Running Lessons 5. Use of Virtual Medical Cases as a Learning Tool in Medicine 6. Comparing the Effectiveness of Two Remedial Mathematics Courses Using Modern Regression Discontinuity Techniques 7. A Comparative Study on Linguistic Theories for Modelling EFL Learners: Facilitating Personalized Vocabulary Learning via Task Recommendations 8. Effects of Interactive Whiteboard-Based Classroom Instruction on Students’ Cognitive Learning Outcomes: A Meta-Analysis
9. Designing Blended Learning Environments with Thinking Tool Strategies: Examining a Chinese Teacher’s Decision-making and Beliefs 10. Design and Validation of a Diagnostic MOOC Evaluation Method Combining AHP and Text Mining Algorithms 11. CRESDA: Towards a Personalized Student Advisory for Professional Development 12. The Prospects of Personalized Learning
| Erscheinungsdatum | 26.10.2023 |
|---|---|
| Verlagsort | London |
| Sprache | englisch |
| Maße | 174 x 246 mm |
| Gewicht | 476 g |
| Themenwelt | Schulbuch / Wörterbuch ► Unterrichtsvorbereitung ► Unterrichts-Handreichungen |
| Mathematik / Informatik ► Informatik ► Theorie / Studium | |
| Sozialwissenschaften ► Kommunikation / Medien ► Buchhandel / Bibliothekswesen | |
| Sozialwissenschaften ► Pädagogik ► Vorschulpädagogik | |
| ISBN-10 | 1-032-58186-7 / 1032581867 |
| ISBN-13 | 978-1-032-58186-6 / 9781032581866 |
| Zustand | Neuware |
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