Artificial intelligence in multimodal learning process analytics : theories, methods and applications / Andy Nguyen (associate professor, Learning and Educational Technology (LET) Research Lab, University of Oulu, Finland), Kshitij Sharma (associate professor, Norwegian University of Science and Technology, Norway) and Ha Nguyen (assistant professor, Learning Sciences and Psychological Studies, University of North Carolina at Chapel Hill, USA).

Format:

Book

Author/Creator:

Nguyen, Andy, author.

Sharma, Kshitij, author.

Nguyên Hà, author.

Contributor:

Edward Elgar Publishing, publisher.

Language:

English

Subjects (All):

Artificial intelligence--Educational applications.

Artificial intelligence.

Genre:

Electronic books.

Physical Description:

1 online resource (208 pages)

Place of Publication:

Northampton : Edward Elgar Publishing, 2026.

Summary:

"In this cutting-edge book, Andy Nguyen, Kshitij Sharma and Ha Nguyen explain how AI can improve our understanding of how people learn. The authors demonstrate how, by analysing multimodal data from different channels, including eye gazes, physiological data and self-reports, AI can provide a clearer picture of what learners think, feel, and do, going far beyond traditional tests or surveys. The authors introduce both classical and deep learning methods for collecting and analyzing data, with a particular focus on multimodal learning process analytics. They explore how large language models and generative AI tools can facilitate human-AI collaboration, while addressing ethical and privacy issues such as fairness, transparency and inclusivity. Integrating theoretical, methodological, and practical perspectives, authors demonstrate how using AI responsibly and thoughtfully can create more inclusive, adaptive and evidence-based learning environments. Artificial Intelligence in Multimodal Learning Process Analytics is a vital reference for scholars and students of learning sciences and pedagogy, particularly those focusing on educational technology, learning analytics and human-computer interaction. It is also highly beneficial for educators and educational policymakers interested in how AI can support learning"-- Provided by publisher.

Contents:

Contents: Preface

Part I: Introduction to multimodal learning process analytics

1. Foundations of multimodal learning process analytics

2. Theoretical frameworks in multimodal learning process analytics

3. Ethical considerations for AI in multimodal learning process analytics

Part II: AI-enhanced multimodal data collection and processing for capturing learning processes

4. Collecting multimodal data to capture learning processes

5. Preprocessing multimodal learning process data

Part III: AI methods for analyzing multimodal data on learning processes

6. Classical machine learning modeling

7. Deep learning modelling

8. Generative artificial intelligence methods for multimodal learning process analytics

Part IV: Future directions and final remarks

9. Future directions for multimodal learning process analytics

10. Conclusion and final remarks

Bibliography.

Notes:

Includes bibliographical references.

Creative Commons Attribution - NonCommercial - NoDerivatives 4.0 International CC BY-NC-ND 4.0 cc https://creativecommons.org/licenses/by-nc-nd/4.0/

Description based on print record.

ISBN:

9781035353811 (e-book)

Access Restriction:

Restricted for use by site license.