This book explores the profound ways in which GenAI-driven tools-such as GPT-4, Transformers, and GANs-are transforming traditional teaching and learning paradigms. Whether you are an educator, researcher, policymaker, or technology leader, the book offers valuable insights into the future of education.
This book explores the profound ways in which GenAI-driven tools-such as GPT-4, Transformers, and GANs-are transforming traditional teaching and learning paradigms. Whether you are an educator, researcher, policymaker, or technology leader, the book offers valuable insights into the future of education.
Rajesh Kumar Dhanaraj is a distinguished Professor at Symbiosis International (Deemed University) in Pune, India. His exceptional academic and research contributions have placed him among the top 2% of scientists globally, an honor recognized by Elsevier and Stanford University. Balasamy Krishnasamy is working as an Assistant Professor in the Department of Artificial intelligence and Data Science at Bannari Amman Institute of Technology, Sathyamangalam, India. Umapriya Rajendran is an Assistant Professor in the Department of Chemical Engineering at KPR Institute of Engineering and Technology, Coimbatore, India. Suganyadevi Sellappan is an Assistant Professor in the department of ECE at KPR Institute of Engineering and Technology, Tamilnadu, India. Rohan Jaikumar, Director, Metasage Alliance, is an alumnus of IIM Kozhikode and a recognized expert in large-scale training, strategic transformation, and educational reform. He has over 16 years of experience leading high-impact initiatives across education, research, and social-impact sectors, designing capacity-building programs and driving institutional change.
Inhaltsangabe
1. Introduction to Generative Artificial Intelligence (GenAI) in Personalized Learning 2. Foundations of GenAI 3. State of the Art GenAI Models 4. Personalized Learning: Understanding Variability, Environments, and Challenges 5. Generative Models for Personalized Learning 6. The Transformative Impact of GenAI in Education 7. Analysis of the Current Status of Educational Applications 8. Applications of GenAI in Education 9. GenAI in Education Key Market Segments Based on Technology 10. Regulatory Framework and Ethical Considerations 11. Future Trends and Directions in GenAI for Education 12. Challenges and Solutions in Implementing GenAI in Education 13. Case Studies and Success Stories in GenAI for Personalized Learning 14. Case Studies: Integrating Risks and Ethical Challenges in GenAI for Education 15. The Future of GenAI in Personalized Learning
1. Introduction to Generative Artificial Intelligence (GenAI) in Personalized Learning 2. Foundations of GenAI 3. State of the Art GenAI Models 4. Personalized Learning: Understanding Variability, Environments, and Challenges 5. Generative Models for Personalized Learning 6. The Transformative Impact of GenAI in Education 7. Analysis of the Current Status of Educational Applications 8. Applications of GenAI in Education 9. GenAI in Education Key Market Segments Based on Technology 10. Regulatory Framework and Ethical Considerations 11. Future Trends and Directions in GenAI for Education 12. Challenges and Solutions in Implementing GenAI in Education 13. Case Studies and Success Stories in GenAI for Personalized Learning 14. Case Studies: Integrating Risks and Ethical Challenges in GenAI for Education 15. The Future of GenAI in Personalized Learning
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