Enhancing Classroom Dialogue Productiveness

This book demonstrates how artificial intelligence (AI) can be used to uncover the patterns of classroom dialogue and increase the productiveness of dialogue. In this book, the author uses a range of data mining techniques to explore the productive features and sequential patterns of classroom dialogue. She analyses how the Large Language Model (LLM) as an AI technique can be adapted to enhance dialogue contributions. The book also includes valuable feedback and practical cases from teachers and their dialogue transcripts, facilitating an understanding of AI use and pedagogical development. This book makes original contributions to the field of classroom dialogue and technology, and it will encourage scholars making similar attempts at technological infusion for pedagogical improvement.

Yu Song has attained her bachelor's degree from Peking University and accomplished MPhil and PhD studies at the University of Cambridge. She works as an associate professor in South China Normal University and a visiting scholar in Peking University. Her research interests include classroom dialogue, intelligent teaching assessment, teacher professional development, and artificial intelligence. She is well-known in the intersection between artificial intelligence and dialogic education.

1. Understanding Classroom dialogue: An Overview 2. Educational use of artificial intelligence 3. Automatic assessment of classroom dialogue using machine learning technique 4. Exploring the collective process of classroom dialogue using sequential pattern mining technique 5. Enhancing dialogue productiveness using generative artificial intelligence 6. Applying AI technique to improve teachers' professional capabilities in dialogic pedagogy