Human-Centered Artificial Intelligence in Education 2

Description

Human-Centered Artificial Intelligence in Education 2 provides a comprehensive and forward-thinking examination of how artificial intelligence (AI) is reshaping the current education systems of the world. With institutions increasingly employing AI-driven tools and techniques, this book provides cutting-edge research and practical knowledge on the ways in which intelligent technologies are affecting learning outcomes, efficiency and the process of decision-making.

The book explores analytics, applications and ethics. It begins with the examination of advanced models of AI and predictive analytics frameworks that can be used to forecast student performance and enhance academic planning. With the integration of deep learning techniques, metaheuristic optimization and hybrid models, this book explores the potential of data-driven education. It also covers real-world applications and examples of AI in various educational and socio-economic settings, explores how AI is going beyond the classrooms and contributing to solving global issues, and discusses the concept of Industry 5.0 and how it promotes human and AI collaboration in building the future of education. Finally, this book deals with the ethics and future directions of AI in education. It discusses critical issues such as inclusiveness and transparency in AI and its applications, while also providing strategic directions for sustainable technology integration in learning settings.

This book brings together contributions from an international team of experts and provides a multidisciplinary view that combines theory, innovation and practice in AI in education. It is a valuable resource for anyone who wants to understand and utilize the transformative role of AI in education, while also making it more inclusive and sustainable.

Contents

Part 1. AI Models, Prediction Systems and Analytics in Education.
1. Enhancing Student Performance Prediction Using Metaheuristic-optimized SAINT Deep Learning Models, Sayed Elkenawy.
2. Enhanced Student Exam Performance Prediction via Ninja-optimized Neural Ordinary Differential Equation (NODE), S.K. Towfek and Ebrahim A. Mattar.
3. Intelligent College Placement Prediction Using a Hybrid FT-Transformer Framework Optimized by Metaheuristic Algorithms, Mahmoud Elshabrawy Mohamed, Amal H. Alharbi, Amel Ali Alhussan and Shahid Mahmood.
4. An Intelligent DeepFM Framework Optimized by Metaheuristic Algorithms for Predicting Students’ Adaptability in Online Learning, Khaled Sh. Gaber, Doaa Sami Khafaga, Marwa M. Eid and Asifa Iqbal.

Part 2. Applications and Socio-Economic-Global Perspectives.
5. AI-Assisted Agricultural Extension: Digital Learning Adoption through Rice Consultation Service for Site-Specific Fertilization in Indonesia, Tri Margono, Rimarsa Haninnakhonsa Margono, Triyani Sumiati, Rinieta Sausan Margono and Koko Kusnanto.
6. AI-Driven Feedback versus Human Touch: A New Frontier in ESL Writing Accuracy, Rizgar Qasim Mahmood.
7. Socioeconomic Transformation of Education in the Era of Industry 5.0, V.H. Abdullayev, R.G. Abaszade and I.X. Normatov.
8. The Role of AI in Virtual Experimentation and Modeling, R.G. Abaszade, V.H. Abdullayev and I.X. Normatov.

Part 3. Ethics and Future Directions.
9. Reimagining Education through Responsible and Inclusive AI: Synthesis and Future Directions, El-Sayed M. El-Kenawy.

About the authors/editors

Pushan Kumar Dutta is an associate professor in the Electronics and Communication Engineering Department at ASETK, Amity University, Kolkata, India.

Vasileios Paliktzoglou holds a PhD in Computer Science from the University of Eastern Finland.

Sonal Trivedi is an associate professor at the School of Business, Manav Rachna University, India.

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Related subjects

• Computer Engineering
• Interdisciplinarity, Science and Humanities