Buch, Englisch, 324 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 699 g
Where Human Learning Meets Learning Machines
Buch, Englisch, 324 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 699 g
Reihe: Postdigital Science and Education
ISBN: 978-3-031-64486-3
Verlag: Springer Nature Switzerland
is a resource for researchers and practitioners in a field where the mainstreaming of AI technologies, and their increased capacities for deception, have produced confusion and fear. Identifying theoretical frameworks and practices in teaching with and training trustworthy and inclusive AI technology sheds light on the new challenges and opportunities for learning machines and their intersections with human learning. The book looks into the history of developing AI technology and algorithms. It offers theoretical models for best practices, interpretation, and evaluation, taking into account especially the needs of contemporary learners and their advanced literacies in cyber-social environments. The book presents in-depth analyses of recent and ongoing applications of state-of-the-art AI technologies in learning environments and classrooms assessments, ending with an interview with George Ritzer on McDonaldization and Artificial Intelligence.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Part 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).