Learning with Generative Artificial Intelligence (eBook, PDF)

What Empirical Studies Tell Us
Redaktion: Fan, Yizhou

• Format: PDF

Produktbeschreibung

This book delves into the core of education's digital transformation, presenting a thorough and empirical examination of generative artificial intelligence (GenAI)'s impact beyond the theoretical and fragmented insights prevalent in current discourse.

Drawing from peer-reviewed and extensive empirical studies, the contributors aim to unveil the multifaceted effects of GenAI (particularly ChatGPT) on learning. They navigate through topics of interaction, assessment, emotion, effect and efficiency, meta-cognition, and ethics, offering a comprehensive exploration of GenAI's educational implications. This book presents a closed loop of learning theory, multimodal data, and learning analytics technology. Furthermore, this book builds and proposes core conceptual models for future learning and identifies potential research directions.

This book will serve as a foundational reference for educators seeking innovative learning and teaching methods and for researchers and technologists who seek to push the boundaries of educational technology and related areas.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 278
• Erscheinungstermin: 20. Juni 2025
• Englisch
• ISBN-13: 9781040369333
• Artikelnr.: 74279523

Autorenporträt

Yizhou Fan is an Assistant Professor at the Graduate School of Education, Peking University and an Adjunct Research Fellow at the Centre for Learning Analytics, Monash University. He identifies himself as a learning analyst employing computational techniques to enhance the understanding of self-regulated learning and to develop next-generation learning environments for envisioning future education. In 2023, he received the Emerging Scholars Award and Early Career Research Grant from SoLAR (The Society for Learning Analytics Research). His recent research focuses on human-AI collaboration and the scaffolding of hybrid intelligence.

Inhaltsangabe

1 Brief History of AI in Education and Transforming Learning with
Generative Artificial Intelligence 2 Empirical Research Design that Linking
Theoretical Concepts and Empirical Data: learning with GenAI or human
teacher 3 Enhancing Learning Through Interaction with GenAI: Opportunities,
Challenges and Future Directions 4 Learners' Emotion and Motivation while
Learning with GenAI 5 The Impacts of GenAI on Learning: What Works and What
Falls Short? 6 How GenAI Affects Metacognition In Self-Regulated Learning:
between Enhancement and Inhibition 7 Enhance Assessing Students' Learning
with GenAI: Challenges, Opportunities and Future Directions 8 Ethical
Issues and Value Tensions in the Context of GenAI-assisted Learning 9
Future Vision and Key Topics of Learning with GenAI: Conceptual
Constructions Rooted in Empirical Studies