This book explores how emerging technologies are reshaping the landscape of higher education quality assurance. Focused on educator preparation programs (EPPs), this timely volume examines how AI tools can transform data-driven decision-making, streamline accreditation processes, and promote institutional equity and accountability. Written by accreditation experts, the book moves beyond technical explanations to address the human dimensions of AI-ethics, fairness, transparency, and professional judgment. Through real-world examples and research-based insights, it offers practical guidance for integrating AI responsibly into accreditation systems while maintaining the integrity of educational evaluation. From automated data analysis to predictive modeling and ethical oversight, the book highlights both the opportunities and risks of AI-driven transformation. Grounded in current scholarship and informed by decades of accreditation practice, this work invites faculty, administrators, and policymakers to imagine a future where innovation and human judgment coexist to advance continuous improvement, educational quality, and professional integrity.

Autorentext

DRS. ANNE TAPP JAKSA, BETH KUBITSKEY, MALINA MONACO, and JOEY PEARSON are accreditation and educator preparation experts with extensive experience leading institutional and programmatic reviews across higher education. As recognized voices in quality assurance and continuous improvement, they bring deep expertise in data-informed decision-making, educational policy, and the ethical integration of AI into accreditation practice.

Inhalt

Foreword
Preface
Chapter 1: Artificial Intelligence's Role in Teacher Education Accreditation and Continuous Improvement
Chapter 2: AI in Data-Driven Decision-Making for Accreditation
Chapter 3: Ethical Considerations and Challenges in AI-Driven Teacher Education Accreditation
Chapter 4: AI in Self-Study Reports and Accreditation Compliance
Chapter 5: Creating a Quality Assurance System (QAS) for Continuous Improvement and Efficiency
Chapter 6: Strategic and Ethical Implementation of AI in Accreditation
Chapter 7: Transformative Innovations and the Future of AI
Appendix A
Appendix B
Reference List