Toward Trustworthy Adaptive Learning

Bo Jiang is an associate professor at East China Normal University, China. His research interests include intelligent tutoring technologies, computational thinking education, and AI education. He holds academic positions as an executive committee member of the Asia-Pacific Society for Computers in Education (APSCE) and a youth committee member of the Chinese Association for Artificial Intelligence. Yuang Wei is a PhD student at East China Normal University, specializing in intelligent education and Explainable AI. His research focuses on adaptive learning systems and enhancing educational equity. His work has been published in several peer-reviewed journals.

Table of Contents

Preface

Authors

Contributors

Section I. Explainable Learner Models: An Overview

1. Trustworthy AI for Adaptive Learning

2. Explainable Learner Models: Concepts, Classifications, and Datasets

3. Construction and Interpretation of Explainable Models: A Case Study on BKT

Section II. Research on Ante-hoc Explainability Learner Models

4. Interpretable Cognitive State Prediction via Temporal Fuzzy Cognitive Map

5. Improving the performance and explainability of knowledge tracing via Markov blanket

6. Knowledge Tracing within Single Programming Practice Using Problem-Solving Process Data

Section III. Research on Post-hoc Explainability Learner Models

7. Understanding the relationship between computational thinking and computational participation

8. Understanding students’ backtracking behaviour in digital textbooks: a data-driven perspective

Section IV. Toward Trustworthy Adaptive Learning

9. Frameworks for Explainable Learner Models

10. Frameworks for Trustworthy AI for Adaptive Learning

Index