Date of Award

8-2026

Document Type

Dissertation

Degree Name

Doctor of Education in Educational Leadership

Department

Educational Leadership

First Reader/Committee Chair

Hannah Kivalahula-Uddin

Abstract

This hermeneutic phenomenological study examined how diverse community college students experience and make meaning of the integration of generative artificial intelligence (AI) into their educational contexts. Although AI is quickly transforming higher education through automated grading, personalized learning systems, and new models of assessment, the discourse surrounding its implementation remains dominated by administrators, faculty, and institutional stakeholders, while the perspectives of students, specifically community college students who are often historically underrepresented and economically marginalized, are systematically excluded. Most existing research is quantitative and centered on universities, leaving a critical gap in qualitative understanding of the most diverse population in higher education. Grounded in the theoretical frameworks of George Spindler’s educational anthropology and Cultural Transmission Theory, Paulo Freire’s critical pedagogy and theory of student agency, and Diana E. Forsythe’s anthropology of artificial intelligence, the study repositioned students from passive recipients to active agents in the construction of knowledge in an AI educational setting. Semi-structured, in-depth interviews were conducted with eleven community college students in Southern California and analyzed through a hybrid inductive–deductive coding strategy that yielded ten themes: AI as cognitive aid versus cognitive tool; generational and institutional disconnect; AI detection, surveillance, and anxiety; institutional hypocrisy and inconsistency; cultural identity, representation, and AI bias; equity and access; ethical, environmental, and moral tensions; pedagogical reform; AI as personalized utility beyond the classroom; and workload and life pressures. Participants made meaning of AI not as a fixed tool but as a continually renegotiated boundary, holding AI use and principled opposition together within a single “use-and-refuse” moral identity that complicates the user/refuser binary on which much institutional policy rests. Students themselves performed substantial critical and analytic work, articulating a coherent reform agenda centered on AI literacy, transparency, parity between students and faculty, and reduced reliance on detection technologies. The findings call for culturally congruent approaches to AI in higher education and for educational leaders to center student voices in institutional policy and pedagogy.

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