Call for Chapters: Quality Assurance Literacy for Sustainable AI Integration in Distance Education

Editors

Nazire Kaya, Eskisehir Osmangazi Unviersity, Turkey
Baris Cukurbasi, Manisa Celal Bayar University, Turkey
Harun Serpil, Anadolu University, Turkey
Dennis Cheek, Universitas Ciputra, Indonesia

Call for Chapters

Proposals Submission Deadline: July 12, 2026
 Full Chapters Due: October 25, 2026
 Submission Date: October 25, 2026

Introduction

Quality Assurance Literacy for Sustainable AI Integration in Distance Education addresses one of the most pressing challenges in contemporary education: ensuring educational quality while integrating artificial intelligence (AI) into rapidly evolving distance and online learning environments. As AI-driven technologies such as learning analytics, adaptive learning systems, intelligent tutoring systems, automated assessment, and generative AI become increasingly embedded in educational processes, institutions face growing demands for accountability, transparency, effectiveness, and sustainability. This book examines the convergence between quality assurance literacy and AI integration, highlighting how educators, instructional designers, administrators, policymakers, and researchers can develop the competencies necessary to evaluate, implement, and sustain AI-supported educational innovations. It explores opportunities, tensions, and future directions related to ethical AI governance, evidence-based decision making, learning design, quality monitoring, accreditation, digital transformation, and educational sustainability. Through theoretical discussions, empirical studies, methodological contributions, technological frameworks, and international case studies, the volume aims to advance scholarly understanding and practical implementation of quality-assured AI integration in distance education ecosystems.

Objective

This book aims to: Advance the emerging concept of quality assurance literacy in digital and distance education. Examine the opportunities and challenges associated with sustainable AI integration in educational contexts. Explore the convergence, divergence, and synergy between AI technologies and quality assurance frameworks. Provide theoretical, methodological, technological, and policy-oriented perspectives on AI-enhanced learning environments. Present empirical evidence, international case studies, and innovative practices supporting quality-driven digital transformation. Promote ethical, transparent, inclusive, and human-centered approaches to AI adoption. Support researchers, practitioners, institutional leaders, and policymakers in developing sustainable AI strategies. Contribute to the global discourse on educational quality, digital innovation, and responsible AI governance.

Target Audience

This publication is intended for: Researchers and scholars in educational technology, learning sciences, instructional design, and distance education. Faculty members, instructional designers, and online learning practitioners. Educational administrators, quality assurance professionals, and accreditation specialists. Policymakers and decision-makers involved in digital transformation initiatives. Researchers working in artificial intelligence, learning analytics, adaptive learning, educational data mining, and human-AI interaction. Graduate students and doctoral candidates studying educational innovation and technology-enhanced learning. International organizations, quality agencies, and institutions seeking sustainable frameworks for AI adoption in education. The book will be particularly valuable for individuals and institutions seeking evidence-based approaches to balancing technological innovation with educational quality, ethics, accountability, and sustainability.

Recommended Topics

-Quality Assurance Literacy in Digital and Distance Education -Sustainable AI Integration in Education -AI Governance and Educational Policy -Responsible and Ethical AI in Learning Environments -Human-AI Collaboration in Education -Learning Analytics and Quality Monitoring -Educational Data Mining for Quality Improvement -Adaptive Learning Systems and Personalization -Intelligent Tutoring Systems -AI-Supported Assessment and Feedback -Generative AI in Teaching and Learning -Accreditation and Quality Standards in Online Education -Institutional Quality Culture and Digital Transformation -Evidence-Based Educational Decision Making -Learning Design and Quality Assurance -Human-Centered AI Approaches -Inclusive and Accessible AI-Supported Education -AI Literacy and Digital Competencies -Quality Assurance Frameworks for Emerging Technologies -Big Data and Educational Quality Metrics -XR, VR, and Immersive Learning Environments -Student Engagement and Learning Experience Design -Sustainability and Equity in Digital Education -Quality Assurance in Resource-Constrained Contexts -Cross-Cultural Perspectives on AI and Educational Quality -International Case Studies of AI Integration -Future Trends in AI-Enhanced Distance Education

Submission Procedure

Researchers and practitioners are invited to submit on or before July 12, 2026, a chapter proposal of 1,000 to 2,000 words clearly explaining the mission and concerns of his or her proposed chapter. Authors will be notified by July 26, 2026 about the status of their proposals and sent chapter guidelines.Full chapters of a minimum of 10,000 words (word count includes references and related readings) are expected to be submitted by October 25, 2026, and all interested authors must consult the guidelines for manuscript submissions at https://www.igi-global.com/publish/contributor-resources/before-you-write/ prior to submission. All submitted chapters will be reviewed on a double-anonymized review basis. Contributors may also be requested to serve as reviewers for this project.

Note: There are no submission or acceptance fees for manuscripts submitted to this book publication, Quality Assurance Literacy for Sustainable AI Integration in Distance Education. All manuscripts are accepted based on a double-anonymized peer review editorial process.

All proposals should be submitted through the eEditorial Discovery® online submission manager.

Publisher

This book is scheduled to be published by IGI Global Scientific Publishing, an international academic publisher of the "Information Science Reference", "Medical Information Science Reference", "Business Science Reference", and "Engineering Science Reference" imprints. IGI Global Scientific Publishing specializes in publishing reference books, scholarly journals, and electronic databases featuring academic research on a variety of innovative topic areas including, but not limited to, education, social science, medicine and healthcare, business and management, information science and technology, engineering, public administration, library and information science, media and communication studies, and environmental science. For additional information regarding the publisher, please visit https://www.igi-global.com. This publication is anticipated to be released in 2027.

Indexing Information for Prospective Authors

IGI Global Scientific Publishing meets the criteria for inclusion in major indexing services such as Scopus; however, it is important to note that all indexing decisions are made independently by these services. IGI Global Scientific Publishing books are selectively indexed by the indexing organization after publication. Indexing cannot be guaranteed for any book prior to publication, and the indexing organization has complete control over the final selection and timeline.

Important Dates

July 12, 2026: Proposal Submission Deadline
July 26, 2026: Notification of Acceptance
October 25, 2026: Full Chapter Submission
December 27, 2026: Review Results Returned
February 7, 2027: Final Acceptance Notification
February 21, 2027: Final Chapter Submission

Inquiries

Nazire Burçin Kaya (Corresponding Editor)
Eskişehir Osmangazi University, Türkiye
nazire.hamutoglu@ogu.edu.tr / burcinhamutoglu@gmail.com

Barış Çukurbaşı
Manisa Celal Bayar University, Türkiye
baris.cukurbasi@cbu.edu.tr

Harun Serpil
Anadolu University, Türkiye
hserpil@anadolu.edu.tr

Dennis Cheek
Universitas Ciputra, Indonesia
dennischeek@ciputra.ac.id
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