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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.
Dr. Beth Kubitskey is a passionate educator, researcher, and leader with a career dedicated to advancing quality in teacher preparation and advocating for continuous improvement in education. Her academic journey began with a B.S. in Chemistry from the University of Michigan, followed by an M.S. in Physics Education from Eastern Michigan University, and culminated in a Ph.D. in Education Studies from the University of Michigan. These experiences provided a strong foundation in both science and education. Dr. Kubitskey has been a faculty member at the University of Michigan-Flint, teaching graduate courses in education methods and clinical based symposia focused on urban teaching and inclusion. Her research focuses on continuous improvement, quality educator preparation, and advocacy. Dr. Kubitskey also serves as a contractor for the Michigan Department of Education, where she collaborates with community colleges and universities to create effective policies and pathways for educator preparation. In her administrative roles, including serving as Dean of the School of Education and Human Services at the University of Michigan-Flint and as Associate Dean at Eastern Michigan University, she has worked to enhance teacher preparation programs, promote equity and inclusion, and foster partnerships with community organizations. She has also led efforts to develop innovative teacher preparation initiatives, such as the Woodrow Wilson Teaching Fellowship and special education pathways for paraprofessionals. Her scholarship reflects my commitment to improving education for all students, authoring numerous publications and presentations on professional development, STEM education, and the impact of innovative teaching practices. Dr. Kubitskey has also collaborated on securing multimillion-dollar grants from the National Science Foundation to enhance teacher preparation and professional learning opportunities. Beyond the academic and administrative work, Beth is actively involved in state and national advocacy for policies that support effective teaching for all students. She works with professional organizations such as the Michigan Association of Colleges of Teacher Education and the American Association of Colleges for Teacher Education to lobby for education policies that advance equity, access, and excellence. Through her work with Women in Leadership and other groups, I strive to promote inclusive practices and systemic change. In addition, Dr. Kubitskey works with the American Education Research Association Recognitions such as the AACTE Outstanding Dissertation Award reflect the impact of my work. I remain committed to advancing education by preparing exceptional teachers and contributing to state and national policy development that ensures all students receive the high-quality education they deserve.
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