Understanding Student Attitudes and Acceptability of GenAI Tools in Higher Ed: Scale Development and Evaluation

TL;DR

This study develops and validates a survey instrument to assess student attitudes towards GenAI tools in higher education, revealing key perceptions and differences across student groups to inform responsible AI integration.

Contribution

Introduces a validated scale for measuring student attitudes towards GenAI, including its acceptability, societal concerns, and perceived impacts, with empirical analysis of diverse student perspectives.

Findings

Four attitudinal dimensions identified: societal concern, policy clarity, fairness and trust, career impact.

Significant differences in attitudes based on gender, language background, and academic year.

The scale provides a practical tool for evaluating student perceptions of GenAI in educational settings.

Abstract

As generative AI (GenAI) tools like ChatGPT become more common in higher education, understanding student attitudes is essential for evaluating their educational impact and supporting responsible AI integration. This study introduces a validated survey instrument designed to assess students' perceptions of GenAI, including its acceptability for academic tasks, perceived influence on learning and careers, and broader societal concerns. We administered the survey to 297 undergraduates at a U.S. university. The instrument includes six thematic domains: institutional understanding, fairness and trust, academic and career influence, societal concerns, and GenAI use in writing and coursework. Exploratory factor analysis revealed four attitudinal dimensions: societal concern, policy clarity, fairness and trust, and career impact. Subgroup analyses identified statistically significant differences across student backgrounds. Male students and those speaking a language other than English at home rated GenAI use in writing tasks as more acceptable. First-year students expressed greater societal concern than upper-year peers. Students from multilingual households perceived greater clarity in institutional policy, while first-generation students reported a stronger belief in GenAI's impact on future careers. This work contributes a practical scale for evaluating the student impact of GenAI tools, informing the design of educational AI systems.