Handbook of Learning Analytics and Adaptive Learning in Schools
Published on 19. May 2026
Book
Hardback
336 pages
978-1-0353-3066-9 (ISBN)
Description
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.
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.
More details
Series
Language
English
Place of publication
Cheltenham
United Kingdom
Target group
Professional and scholarly
Dimensions
Height: 244 mm
Width: 169 mm
ISBN-13
978-1-0353-3066-9 (9781035330669)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Persons
Edited by Cathrine E. Tomte, 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
Content
Contents
PART I INTRODUCTION
1 Why do we need a handbook on learning analytics and adaptive learning
in schools? 2
Cathrine Edelhard Tomte, 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 10
Paul Prinsloo and Mohammad Khalil
3 Adaptive learning systems: leveraging generative artificial intelligence for
optimal adaptivity 21
Sima Caspari-Sadeghi
4 Designing multimodal collaboration analytics: challenges and
opportunities 35
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 51
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 64
Malgorzata Agnieszka Cyndecka
7 Smart predictions, unseen bias: navigating the promises and pitfalls of
predictive analytics in compulsory education 77
Lin Li
8 When categories matter: attendance data practices in an upper secondary
classroom 96
Fride Haram Klykken
PART IV PEDAGOGICAL POSSIBILITIES AND CHALLENGES
9 Teacher development with learning analytics: a design narrative 113
Fabio Campos, Ha Nguyen and June Ahn
10 Multi-case teacher inquiry to inform dashboard development 127
Merike Saar
11 Understanding the interrelated nature of academic, social, and emotional
competencies through learning analytics 137
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 157
Kjersti Nedland Roneid, Gleb Belokrys and Kristin Borte
13 Teaching Learning Analytics as formative assessment for pre-service
teachers: report from a first trial 176
Cathrine Edelhard Tomte and Maria Wasmuth Gronvold
14 EssayCritic: enhancing student essays with locally trained AI feedback 191
Anders Morch and Irina Engeness
15 Adaptive learning in primary mathematics: teachers' practices and insights 210
Kjetil Egelandsdal
16 Operationalising science competencies to support teachers' formative
assessment and instruction with Inq-ITS AI 230
Janice D. Gobert, Amy Adair, Jessica A. Owens and Rachel Dickler
PART V PROMOTING IMPLEMENTATION
17 Navigating learning analytics: challenges, opportunities, and
recommendations 248
Marte Blikstad-Balas
18 Implementing learning analytics and adaptive learning in Norwegian
schools: lessons learned 259
Barbara Wasson and Cecilie J.S. Hansen
19 Bridging the data divide in Swedish school education: challenges and
opportunities in data standards 275
Italo Masiello and Zeynab (Artemis) Mohseni
20 The paradoxes of AI promises in schools: Insights from a multi-sited
ethnography 294
Katarina Sperling and Linnea Stenliden
PART I INTRODUCTION
1 Why do we need a handbook on learning analytics and adaptive learning
in schools? 2
Cathrine Edelhard Tomte, 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 10
Paul Prinsloo and Mohammad Khalil
3 Adaptive learning systems: leveraging generative artificial intelligence for
optimal adaptivity 21
Sima Caspari-Sadeghi
4 Designing multimodal collaboration analytics: challenges and
opportunities 35
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 51
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 64
Malgorzata Agnieszka Cyndecka
7 Smart predictions, unseen bias: navigating the promises and pitfalls of
predictive analytics in compulsory education 77
Lin Li
8 When categories matter: attendance data practices in an upper secondary
classroom 96
Fride Haram Klykken
PART IV PEDAGOGICAL POSSIBILITIES AND CHALLENGES
9 Teacher development with learning analytics: a design narrative 113
Fabio Campos, Ha Nguyen and June Ahn
10 Multi-case teacher inquiry to inform dashboard development 127
Merike Saar
11 Understanding the interrelated nature of academic, social, and emotional
competencies through learning analytics 137
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 157
Kjersti Nedland Roneid, Gleb Belokrys and Kristin Borte
13 Teaching Learning Analytics as formative assessment for pre-service
teachers: report from a first trial 176
Cathrine Edelhard Tomte and Maria Wasmuth Gronvold
14 EssayCritic: enhancing student essays with locally trained AI feedback 191
Anders Morch and Irina Engeness
15 Adaptive learning in primary mathematics: teachers' practices and insights 210
Kjetil Egelandsdal
16 Operationalising science competencies to support teachers' formative
assessment and instruction with Inq-ITS AI 230
Janice D. Gobert, Amy Adair, Jessica A. Owens and Rachel Dickler
PART V PROMOTING IMPLEMENTATION
17 Navigating learning analytics: challenges, opportunities, and
recommendations 248
Marte Blikstad-Balas
18 Implementing learning analytics and adaptive learning in Norwegian
schools: lessons learned 259
Barbara Wasson and Cecilie J.S. Hansen
19 Bridging the data divide in Swedish school education: challenges and
opportunities in data standards 275
Italo Masiello and Zeynab (Artemis) Mohseni
20 The paradoxes of AI promises in schools: Insights from a multi-sited
ethnography 294
Katarina Sperling and Linnea Stenliden