Measuring How Students Rely on Generative AI in Academic Writing: Development and Multi-Source Validation of the Generative AI Reliance Types Scale (GenAI-RTS)

As generative AI (GenAI) becomes embedded in undergraduate academic writing, how students rely on these tools — not merely whether they use them — has emerged as a core question for Academic Integrity, Student Experience, and educational equity. This study develops and validates the Generative AI Reliance Types Scale (GenAI-RTS), a 20-item instrument measuring four theoretically derived reliance types: Strategic, Instrumental, Dependent, and Dialogic. Confirmatory factor analysis supports a five-factor structure in which Strategic Reliance splits into Deliberate Use and Critical Evaluation (CFI = .92, RMSEA = .08; DWLS CFI = .98, RMSEA = .07), with subscale reliability (ω) ranging .75–.90.

Validation follows the multi-source framework of the Standards for Educational and Psychological Testing, combining a survey of 382 undergraduates at a U.S. Minority-Serving Institution with interviews with 14 purposively sampled students. The Critical Evaluation facet — students scrutinizing GenAI output rather than accepting it — directly operationalizes AI Literacy in writing contexts, while the Dependent type maps onto documented patterns of Over Reliance on Generative AI tools. The instrument gives researchers and instructors a validated way to measure reliance modes in Writing Education and across Higher Ed, moving beyond binary “use/no-use” measures toward nuanced, equity-aware assessment of GenAI integration.

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Shahin Hossain, Tukhbita Afroz Nawmi (2026). Measuring How Students Rely on Generative AI in Academic Writing: Development and Multi-Source Validation of the Generative AI Reliance Types Scale (GenAI-RTS). arXiv:2607.14301.