Generative AI Use in Professional Graduate Thesis Writing: Adoption, Perceived Outcomes, and the Role of a Research-Specialized Agent

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Abstract:This paper reports a survey of generative AI use among 83 MBA thesis students in Japan (target population 230; 36.1% response rate), conducted after thesis examiner evaluation. AI use was nearly universal: 95.2% reported at least some use and 77.1% heavy use. Students engaged AI across the full research-writing workflow - literature review, drafting, and consultation when stuck - reporting benefits centered on clearer argument and structure (82.3%), better revision quality (73.4%), and faster writing (70.9%), with a mean perceived quality improvement of 6.27 out of 7. Concerns about output accuracy (75.9%) and citation handling persisted alongside these gains. Among respondents who rated GAMER PAT, a research-specialized agent, against other AI, preferences significantly favored it for inquiry deepening and structural organization (both p < 0.05, exact binomial). A preliminary qualitative analysis of follow-up interviews further reveals active epistemic vigilance strategies and differentiated tool use across thesis phases. The central implication is not adoption itself but a shift in the educational challenge toward verification, source governance, and AI tool design - with GAMER PAT offering preliminary evidence that research-specialized scaffolding matters.

Comments: 11 pages, 5 figures

Subjects:

Computers and Society (cs.CY); Human-Computer Interaction (cs.HC)

ACM classes: K.3.1; K.4.1

Cite as: arXiv:2604.02792 [cs.CY]

(or arXiv:2604.02792v1 [cs.CY] for this version)

https://doi.org/10.48550/arXiv.2604.02792

arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Kenji Saito [view email] [v1] Fri, 3 Apr 2026 06:58:22 UTC (91 KB)