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The human-AI partnership model for faculty mentorship: A conceptual framework for reflective learning in nursing
Heather M Englund1, Bonnie Soik1, Jessica Habeck1
1University of Wisconsin Oshkosh, College of Nursing, Health Professions, and STEM 800 Algoma Blvd, Oshkosh, WI 54901, United States.
Aim:
To present the Human-AI Partnership Model, a conceptual framework for integrating artificial intelligence into faculty mentorship to enhance reflective learning, feedback continuity and institutional insight in nursing and health professions education.
Background:
Faculty mentorship is central to academic development but remains fragmented, informal and difficult to scale. Inconsistent access, variable feedback quality and limited evaluability constrain its effectiveness, particularly in complex academic and clinical roles.
Design:
Conceptual discussion paper.
Methods:
The HAPM was developed through integration of Systems Theory, Cognitive Apprenticeship and Adult Learning Theory. The model conceptualizes mentorship as a multi-level system linking individual reflection, relational mentoring processes and organizational learning and is operationalized through a structured AI-supported workflow.
Results:
The HAPM outlines a cyclical process incorporating reflective inputs, AI-assisted synthesis, mentor interpretation and longitudinal feedback. The model demonstrates how AI can support reflective depth, improve feedback consistency, reduce administrative burden and generate aggregated insights to inform faculty development. Ethical governance, human oversight and equity considerations are embedded throughout the framework.
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