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

‘Andy Nguyen, Kshitij Sharma and Ha Nguyen have written a clear, thoughtful, and practical introduction to a cutting-edge direction in education research. Multimodal learning processing analytics holds tremendous potential to revolutionize how we understand and support learning, and this book can turn the curious newcomer into a knowledgeable explorer of these techniques.’

• ContentsPreface PART I INTRODUCTION TO MULTIMODAL LEARNINGPROCESS ANALYTICS1 Foundations of multimodal learning process analytics 2 Theoretical frameworks in multimodal learning processanalytics 3 Ethical considerations for AI in multimodal learning processanalytics PART II AI-ENHANCED MULTIMODAL DATACOLLECTION AND PROCESSING FORCAPTURING LEARNING PROCESSES4 Collecting multimodal data to capture learning processes 5 Preprocessing multimodal learning process dataPART III AI METHODS FOR ANALYZING MULTIMODALDATA ON LEARNING PROCESSES6 Classical machine learning modeling 7 Deep learning modelling 8 Generative artificial intelligence methods for multimodallearning process analytics PART IV FUTURE DIRECTIONS AND FINAL REMARKS9 Future directions for multimodal learning process analytics 10 Conclusion and final remarks Bibliography

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

‘Andy Nguyen, Kshitij Sharma and Ha Nguyen have written a clear, thoughtful, and practical introduction to a cutting-edge direction in education research. Multimodal learning processing analytics holds tremendous potential to revolutionize how we understand and support learning, and this book can turn the curious newcomer into a knowledgeable explorer of these techniques.’

• ContentsPreface PART I INTRODUCTION TO MULTIMODAL LEARNINGPROCESS ANALYTICS1 Foundations of multimodal learning process analytics 2 Theoretical frameworks in multimodal learning processanalytics 3 Ethical considerations for AI in multimodal learning processanalytics PART II AI-ENHANCED MULTIMODAL DATACOLLECTION AND PROCESSING FORCAPTURING LEARNING PROCESSES4 Collecting multimodal data to capture learning processes 5 Preprocessing multimodal learning process dataPART III AI METHODS FOR ANALYZING MULTIMODALDATA ON LEARNING PROCESSES6 Classical machine learning modeling 7 Deep learning modelling 8 Generative artificial intelligence methods for multimodallearning process analytics PART IV FUTURE DIRECTIONS AND FINAL REMARKS9 Future directions for multimodal learning process analytics 10 Conclusion and final remarks Bibliography