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Democratizing Personalized Learning Through Mentorship Reform in Private Higher Education
Abstract
This chapter explores the integration of Artificial Intelligence (AI) in faculty-faculty mentorship within higher education, emphasizing its potential to enhance mentorship quality, promote equity, and streamline administrative processes. AI tools, such as automated scheduling and sentiment analysis, offer solutions to long-standing issues such as administrative burdens, power imbalances, and implicit biases in mentorship relationships. The chapter discusses how AI can foster more inclusive and equitable mentorship environments, particularly in hierarchical academic settings. Despite these promising advancements, challenges such as algorithmic bias, ethical concerns, and institutional resistance are critically examined. The chapter concludes by emphasizing the importance of a phased, culturally responsive implementation strategy and the need for ongoing evaluation. Future research directions are proposed, focusing on longitudinal studies, cross-cultural comparisons, and faculty attitudes toward AI adoption to ensure sustainable, ethical integration in mentorship programs.
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