Leveraging Artificial Intelligence to Transform Teacher Education Accreditation : A Framework for Innovation and Equity / Anne Tapp Jaksa, Beth Kubitskey, Malina Monaco, and Joey Pearson.

Format:

Book

Author/Creator:

Kubitskey, Beth, author.

Jaksa, Anne Tapp, author.

Monaco, Malina, author.

Pearson, Joseph Allen, author.

Language:

English

Subjects (All):

Accreditation (Education).

Artificial intelligence--Educational applications.

Artificial intelligence.

Physical Description:

1 online resource (152 pages)

Edition:

1st ed.

Place of Publication:

New York : Bloomsbury Publishing (US), 2026.

System Details:

text file rdaft

Summary:

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.

Contents:

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

ISBN:

9798216375203

OCLC:

1577546338