Description
Book SynopsisPart 1 - Tracing AI and learning across disciplines and histories.- CHAPTER 1. Machine Learning and Human Learning (Bill Cope and Mary Kalantzis).- CHAPTER 2: Exploring the Potential of AI Models in Education: A Post-Phenomenological and Digital Hermeneutic Perspective on Transposition Literacies (Eduardo de Moura Almeida - Rodrigo Abrantes da Silva).- CHAPTER 3: Re-Introducing Reinforcement Learning Algorithms to Human Learning (Dora Kourkoulou).- Part 2 - Emerging Debates: this section includes overviews on specialized areas of AI technology and its relationship to learning, such as generative models, Deep learning, explainable AI, and inclusive AI technology.- CHAPTER 4: Generative AI and Its Educational Implications (John T. Behrens, Peter W. Foltz, & Kacper Lodzikowski).- CHAPTER 5: Deep Learning For Educational Data Science (Juan Pinto, & Luc Paquette).- CHAPTER 6: A surveyof the use of explainable AI in education (Sophie Liu & Luc Paquette).- CHAPTER 7: AI and Inclusive Education (Shafagh Hadinezhad, Sourabh Garg, & Robb Lindgren).- CHAPTER 8: Utilizing VR and AI for training and professional development in education (Akash Shaini and Matthew Montebello).- Part 3- Research from the field (this part will focus on recent usages of various AI technologies, in learning practices across levels of education).- CHAPTER 9: Artificial intelligence in translingual language learning (Anastasia O. Tzirides).- CHAPTER 10: Using Machine-generated Review and Revision in Academic and Technical Writing Courses (Jen Whiting).- CHAPTER 11: "Mirror, Mirror, on theWall" - Promoting Self-Regulated Learning using Affective States Recognition via Facial Movements (Si Chen, Huang Yun, Yixin Liu, Yuqian Zhou, Yi-Chieh Lee, Risheng Lu).- CHAPTER 12: Assisting EFL Writers Plan for English Writing Task by ChatGPT (Yu-ling You).
