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

Fuente: arXiv
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Hauptverfasser: Tang, Xiuxiu, Chen, Si, Cheng, Ying, Chawla, Nitesh V, Metoyer, Ronald, Ambrose, G. Alex
Format: Preprint
Veröffentlicht: 2025
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author Tang, Xiuxiu
Chen, Si
Cheng, Ying
Chawla, Nitesh V
Metoyer, Ronald
Ambrose, G. Alex
author_facet Tang, Xiuxiu
Chen, Si
Cheng, Ying
Chawla, Nitesh V
Metoyer, Ronald
Ambrose, G. Alex
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2508_01926
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Understanding Student Attitudes and Acceptability of GenAI Tools in Higher Ed: Scale Development and Evaluation
Tang, Xiuxiu
Chen, Si
Cheng, Ying
Chawla, Nitesh V
Metoyer, Ronald
Ambrose, G. Alex
Computers and Society
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.
title Understanding Student Attitudes and Acceptability of GenAI Tools in Higher Ed: Scale Development and Evaluation
topic Computers and Society
url https://arxiv.org/abs/2508.01926