Handbook of Learning Analytics and Adaptive Learning in Schools (Elgar Handbooks in Education)

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.

Edited by Cathrine E. Tømte, Professor, Department of Information Systems & CeDiT, University of Agder, Norway, Linda Barman, Associate Professor, Department of Education, Stockholm University, Sweden and Barbara Wasson, Professor and Director, Centre for the Science of Learning & Technology (SLATE) and AI LEARN, University of Bergen, Norway