New Scale Measures Student Generative AI Reliance in Writing.

Shahin Hossain, Tukhbita Afroz Nawmi· July 17, 2026 View original

Key takeaways

  • Understanding how students use GenAI is more important than just if they use it.
  • The GenAI-RTS identifies four key types of student reliance: Strategic, Instrumental, Dependent, and Dialogic.
  • Strategic reliance, involving deliberate use and critical evaluation, correlates with higher AI literacy.
  • This validated scale provides a tool for educators to inform policy and AI literacy interventions.

Who benefits

EdTechHigher EducationK-12 EducationLearning & Development

Summary

This study developed and validated the GenAI Reliance Types Scale (GenAI-RTS), a 20-item instrument measuring four types of generative AI reliance in academic writing: Strategic, Instrumental, Dependent, and Dialogic. It provides a psychometrically validated tool for researchers and educators to understand student AI use.

As generative AI (GenAI) becomes increasingly integrated into academic writing, understanding how students use these tools, rather than just if they use them, is crucial for learning, academic integrity, and equity. Existing measures of AI reliance have limitations, often developed inductively and validated with narrow samples. This research addresses that gap by developing and validating the Generative AI Reliance Types Scale (GenAI-RTS). The GenAI-RTS is a 20-item instrument designed to measure four theoretically derived types of GenAI reliance: Strategic, Instrumental, Dependent, and Dialogic. Through a multi-source validation framework, including a survey of 382 undergraduates and interviews with 14 students, the study confirmed a five-factor structure where Strategic Reliance splits into "Deliberate Use" and "Critical Evaluation." The scale demonstrated acceptable to good reliability and scalar measurement invariance across various student demographics. The findings indicate that strategic reliance correlates positively with AI literacy, and the different reliance types distinguish students across various writing process and outcome variables. This new scale offers a robust, theoretically grounded tool for educators and researchers to identify student reliance profiles and inform AI literacy interventions.

Why it matters

Educators and institutions need robust tools to understand and measure how students are actually using generative AI, enabling them to develop effective policies, curricula, and support systems for academic integrity and AI literacy.

How to implement this in your domain

  1. 1Utilize the GenAI-RTS or similar frameworks to assess student AI reliance patterns in academic settings.
  2. 2Develop AI literacy programs that specifically address different reliance types, promoting strategic and critical use.
  3. 3Revise academic integrity policies to account for nuanced forms of AI assistance, moving beyond simple prohibition.
  4. 4Train faculty on recognizing and responding to various GenAI reliance behaviors in student work.

Original post by Shahin Hossain, Tukhbita Afroz Nawmi

"arXiv:2607.14301v1 Announce Type: new Abstract: As generative AI (GenAI) becomes increasingly embedded in undergraduate academic writing, how students rely on these tools, rather than simply whether they use them, has become a central question for learning, academic integrity, an…"

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