Abstract

While higher education has increasingly embraced emerging technologies, limited research explores how adult learners at the graduate level navigate AI-driven feedback, content generation, and learning supports, particularly within online programs that require self-regulation and advanced academic rigor. To address this gap, this qualitative, phenomenological study examined how graduate students enrolled in online degree programs experience and interpret the use of generative AI (GenAI) tools, such as ChatGPT, in their coursework. Drawing on Self-Determination Theory (SDT), this study focused on how the use of GenAI tools may influence students’ perceptions on autonomy (volition and choice in tasks), competence (confidence in academic mastery), and relatedness (sense of community or belonging), ultimately impacting their motivation and well-being.

A stratified purposeful sample of nine graduate students who actively use GenAI for assignments, discussion posts, and research-related tasks participated in in-depth, semi-structured interviews. Phenomenological approach was used to explore the students’ lived experiences and aim to capture the subjective meanings and contextual factors influencing their technology adoption (Creswell & Poth, 2018; Moustakas, 1994). Bracketing techniques and iterative coding were used to identify shared themes, reflecting the relationship between AI-driven tools and the motivational needs central to SDT.

By examining students’ engagement with GenAI tools, this study addresses a gap in the literature on advanced digital learning resources and adult learner motivation in higher education. The findings may offer practical insights for online program administrators, instructors, and educational technologies aiming to integrate AI-enhanced curricula in ways that uphold academic rigor, promote authentic student agency, and foster connection within virtual graduate learning environments.

Library of Congress Subject Headings

Artificial intelligence; Generative artificial intelligence; Web-based instruction; Graduate students

Date of Award

2025

School Affiliation

Graduate School of Education and Psychology

Department/Program

Education

Degree Type

Dissertation

Degree Name

Doctorate

Faculty Advisor

Jennifer Miyake-Trapp

Included in

Education Commons

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