Date of Graduation

Spring 2026

Document Type

Dissertation

Degree Name

Doctor of Education (EdD)

Department

Education Policy, Planning, and Administration

Committee Chairperson

Matthew Kruger-Ross, PhD

Committee Member

Andy Famiglietti, PhD

Committee Member

Eryn Travis, PhD

Abstract

The widespread availability of generative artificial intelligence (GenAI) tools and their rapid evolution has prompted faculty and institutions to develop classroom policies in effort to manage use, yet little empirical research exists on how such policies impact students. This qualitative study sought to explore how higher education students define academic integrity and GenAI’s place within it, how they perceive and evaluate classroom GenAI policies, and how such policies shape their academic self-efficacy, motivation, and engagement. Semi-structured interviews were conducted with sixteen undergraduate and graduate students at a mid-sized public university located in the Mid-Atlantic region of the United States. Interview transcripts were then analyzed in multiple rounds of systemic coding to identify four major themes: (1) students’ had traditional understandings of academic integrity and aligned boundaries for GenAI use; (2) variance in the communication, restrictiveness, and enforcement of classroom GenAI policies; (3) mixed and nuanced effects on students’ academic self-efficacy, motivation, and engagement; and (4) student recommendations for policy improvement. Findings were interpreted through an integrated theoretical framework that combined Cultural-Historical Activity Theory (CHAT), Self-Efficacy Theory (SET), and Self-Determination Theory (SDT). The findings suggest implications for educational practice for faculty and institutions, and avenues for future research.

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