Interdisciplinary Applications of Artificial Intelligence - 1

Artificial intelligence has become an integral component of contemporary scientific research, educational practices, and technological development. Rather than functioning as a standalone technical field, artificial intelligence now operates as a cross-cutting framework that reshapes how knowledge is produced, interpreted, and applied across disciplines. This edited volume was conceived in response to the growing need for a structured, critical, and practice-oriented understanding of artificial intelligence and its expanding role in both research and education.

As editors, we aimed to bring together theoretical foundations, methodological perspectives, and application oriented studies within a coherent and accessible framework. The chapters included in this book reflect a broad spectrum of approaches, ranging from fundamental concepts of artificial intelligence to advanced topics such as generative artificial intelligence, large language models, data ethics, and secure AI systems. Particular attention has been given to the integration of artificial intelligence into research processes, instructional design, and programming practices, highlighting both opportunities and emerging challenges.

This volume emphasizes that artificial intelligence should be understood not only through its technical capabilities but also through its implications for ethical responsibility, data governance, and human–AI interaction. Several chapters address these concerns directly by examining issues related to privacy, transparency, accountability, and human oversight. By doing so, the book seeks to encourage responsible and informed use of artificial intelligence technologies across diverse contexts.

Another distinguishing feature of this book is its interdisciplinary orientation. Contributions draw on perspectives from computer science, educational sciences, research methodology, and applied technologies, demonstrating how artificial intelligence can function as a unifying tool across domains. The inclusion of an AI-integrated platform for end-to-end meta-analysis further illustrates how artificial intelligence can support complex research workflows in practice.

This book is intended for researchers, graduate students, educators, instructional designers, and practitioners who seek a comprehensive yet conceptually grounded understanding of artificial intelligence. Rather than presenting artificial intelligence as a fully autonomous solution, the chapters collectively highlight the importance of human expertise, critical judgment, and contextual awareness in AI-supported systems.

We would like to express our sincere gratitude to all contributing authors for their valuable expertise and commitment. Their contributions have been essential in shaping this volume and ensuring its academic rigor and practical relevance. We also thank the reviewers and editorial collaborators whose feedback strengthened the clarity and coherence of the chapters.

We hope that this book will serve as a useful reference for ongoing research and practice, and that it will contribute to informed discussions on the responsible and meaningful integration of artificial intelligence into education, research, and software development.

Editors

Assoc. Prof. Dr. Abdullatif Kaban

Atatürk University

Erzurum

Türkiye

Assoc. Prof. Dr. Turgay Demirel

Atatürk University

Erzurum

Türkiye