Handbook of learning analytics and adaptive learning in schools / Edited by Cathrine E. Tømte (professor, Department of Information Systems and CeDiT, University of Agder, Norway Norway), Linda Barman (associate professor, Department of Education, Stockholm University, Sweden) and Barbara Wasson (professor and director, Centre for the Science of Learning and Technology (SLATE) and AI LEARN, University of Bergen, Norway).

Format:

Book

Contributor:

Tømte, Cathrine E., editor.

Barman, Linda, editor.

Wasson, Barbara, editor.

Edward Elgar Publishing, publisher.

Series:

Elgar handbooks in education

Language:

English

Subjects (All):

Educational technology--Handbooks, manuals, etc.

Educational technology.

Computer-assisted instruction--Handbooks, manuals, etc.

Computer-assisted instruction.

Genre:

Electronic books.

Physical Description:

1 online resource (336 pages)

Place of Publication:

Northampton : Edward Elgar Publishing, 2026.

Summary:

"This timely Handbook explores the use of emerging digital technologies in education, demonstrating how learning analytics, adaptive technologies and artificial intelligence can be implemented to achieve pedagogical goals. As digital technologies become integral to education, chapters discuss how the focus is shifting from whether to use these tools, to how they can best support teaching and learning. Contributors address concerns surrounding data privacy, transparency and practical use, emphasising the importance of professional development and collaboration among educators, leaders and stakeholders. Drawing on empirical insights, chapters highlight the potential of learning analytics and adaptive learning to personalise education and improve outcomes for all students. This insightful Handbook promotes thoughtful policy, robust infrastructure and a thorough understanding of the professional and ethical contexts in which these tools are deployed. The Handbook of Learning Analytics and Adaptive Learning in Schools is an essential resource for scholars and students interested in educational technology, particularly those exploring the impact of data mining and learning analytics. It is also highly beneficial for educators and policymakers looking to ensure these emerging tools are used purposefully and in alignment with curriculum goals"-- Provided by publisher.

Contents:

Contents: Part I: Introduction

1. Why do we need a handbook on learning analytics and adaptive learning in schools? / Cathrine Edelhard Tømte, Barbara Wasson and Linda Barman

Part II: Understanding learning analytics and adaptive learning: Definitions, principles and scopes

2. Learning analytics in schools: Provocations and pointers / Paul Prinsloo and Mohammad Khalil

3. Adaptive learning systems: Leveraging generative artificial intelligence for optimal adaptivity / Sima Caspari-Sadeghi

4. Designing multimodal collaboration analytics: Challenges and opportunities / Daniel Spikol, Morten Misfeldt, Zaibei Li and Viktor Holm-Janas

5. Integrating the science of learning with EdTech solutions: From frameworks to models of practice / Natalia Ingebretsen Kucirkova

Part III: Ethical considerations and privacy concerns

6. The general data protection regulation's right to explanation of algorithmic decision-making in the context of using AI-powered learning analytics in compulsory education / Małgorzata Agnieszka Cyndecka

7. Smart predictions, unseen bias: Navigating the promises and pitfalls of predictive analytics in compulsory education / Lin

8. When categories matter: Attendance data practices in an upper secondary classroom / Fride Haram Klykken

Part IV: Pedagogical possibilities and challenges

9. Teacher development with learning analytics: A design narrative / Fabio Campos, Ha Nguyen and June Ahn

10. Multi-case teacher inquiry to inform dashboard development / Merike Saar

11. Understanding the interrelated nature of academic, social, and emotional competencies through learning analytics / Jae H. Paik, Igor Himelfarb, Seung Hee Yoo, Jongtak Lee, Hoyong Ha and Yurim Park

12. Using learning analytics to explore pre-service teachers' lesson planning / Kjersti Nedland Røneid, Gleb Belokrys and Kristin Børte

13. Teaching learning analytics as formative assessment for pre-service teachers: Report from a first trial / Cathrine Edelhard Tømte and Maria Wasmuth Grønvold

14. EssayCritic: Enhancing student essays with locally trained AI feedback / Anders Mørch and Irina Engeness

15. Adaptive learning in primary mathematics: Teachers' practices and insights / Kjetil Egelandsdal

16. Operationalising science competencies to support teachers' formative assessment and instruction with Inq-ITS AI / Janice D. Gobert, Amy Adair, Jessica A. Owens and Rachel Dickler

Part V: Promoting implementation

17. Navigating learning analytics: Challenges, opportunities, and recommendations / Marte Blikstad-Balas

18. Implementing learning analytics and adaptive learning in Norwegian schools: Lessons learned / Barbara Wasson and Cecilie J.S. Hansen

19. Bridging the data divide in Swedish school education: Challenges and opportunities in data standards / Italo Masiello and Zeynab (Artemis) Mohseni

20. The paradoxes of AI promises in schools: Insights from a multi-sited ethnography / Katarina Sperling and Linnéa Stenliden.

Notes:

Includes index.

Description based on print record.

ISBN:

9781035330676 (e-book)

Access Restriction:

Restricted for use by site license.