Teaching and Learning in the Age of Generative AI
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Teaching and Learning in the Age of Generative AI
Evidence-Based Approaches to Pedagogy, Ethics, and Beyond
Corbeil, Joseph Rene; Corbeil, Maria Elena
Taylor & Francis Ltd
04/2025
406
Dura
Inglês
9781032688596
Pré-lançamento - envio 15 a 20 dias após a sua edição
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Part I. Foundations and Frameworks of AI in Education 1. What is Generative AI? A Primer 2. Developing a Framework for Implementing AI in Education and Evaluating Its Use Part II. Transformative Teaching and Learning with AI 3. Transformative Teaching with AI 4. The Age of Chat: Education and the Rise of No-Code Chatbots 5. Promoting Critical Thinking and Problem-Solving Through AI Part III. Ethical and Institutional Considerations 6. Rethinking Cheating in the Age of AI 7. Developing Institutional Policies for AI in Education 8. Navigating Risks: Inaccuracies, Bias, Disinformation, and Privacy in Educational AI 9. Exploring the Generative Artificial Intelligence Fair Use Policy Landscape in Higher Education Part IV. Preparing Educators and Students for AI Integration 10. Teaching Generative AI in Higher Education: Strategies, Implications, and Reflective Practices 11. Preparing Pre-Service and In-Service Teachers for the AI-Driven Classroom 12. Preparing Students to Live and Work in an AI-Driven World: Ideas for Educators and Students Part V. Future Trends and Implications of AI in Education 13. Redefining Assessments in the Age of AI 14. AI and the Digital Divide 15. Defining Key Workplace Competencies in the AI Era: A Framework for AI-Powered Education 16. AI-Driven Self-Directed Lifelong Learning: Personalization and Empowerment in the Digital Age 17. The Future of Learning: AI-Driven Education in 2040
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Teaching and Learning in the Age of Generative AI;Joseph Rene Corbeil;Maria Elena Corbeil;artificial intelligence;ChatGPT;large language model;educational technology;K-12 technology integration;school technology coordination;technology-enhanced learning;pedagogy;ethical concerns;chatbot;teaching assistant;intelligent tutoring system;algorithmic bias;self-directed lifelong learning
Part I. Foundations and Frameworks of AI in Education 1. What is Generative AI? A Primer 2. Developing a Framework for Implementing AI in Education and Evaluating Its Use Part II. Transformative Teaching and Learning with AI 3. Transformative Teaching with AI 4. The Age of Chat: Education and the Rise of No-Code Chatbots 5. Promoting Critical Thinking and Problem-Solving Through AI Part III. Ethical and Institutional Considerations 6. Rethinking Cheating in the Age of AI 7. Developing Institutional Policies for AI in Education 8. Navigating Risks: Inaccuracies, Bias, Disinformation, and Privacy in Educational AI 9. Exploring the Generative Artificial Intelligence Fair Use Policy Landscape in Higher Education Part IV. Preparing Educators and Students for AI Integration 10. Teaching Generative AI in Higher Education: Strategies, Implications, and Reflective Practices 11. Preparing Pre-Service and In-Service Teachers for the AI-Driven Classroom 12. Preparing Students to Live and Work in an AI-Driven World: Ideas for Educators and Students Part V. Future Trends and Implications of AI in Education 13. Redefining Assessments in the Age of AI 14. AI and the Digital Divide 15. Defining Key Workplace Competencies in the AI Era: A Framework for AI-Powered Education 16. AI-Driven Self-Directed Lifelong Learning: Personalization and Empowerment in the Digital Age 17. The Future of Learning: AI-Driven Education in 2040
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Teaching and Learning in the Age of Generative AI;Joseph Rene Corbeil;Maria Elena Corbeil;artificial intelligence;ChatGPT;large language model;educational technology;K-12 technology integration;school technology coordination;technology-enhanced learning;pedagogy;ethical concerns;chatbot;teaching assistant;intelligent tutoring system;algorithmic bias;self-directed lifelong learning
