Undergraduate mathematics faculty attitudes and experiences with generative AI integration
Eunmi Joung 1 * , Roxanne Brinkerhoff 1 , Inyoung Lee 2 , Allan Wong 1 , Ofa Ioane 1
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1 Department of Mathematical and Quantitative Reasoning, College of Science, Utah Valley University, Orem, UT, USA2 Department of Mathematics, College of Science, Utah Valley University, Orem, UT, USA* Corresponding Author

Abstract

Generative artificial intelligence (GenAI) is rapidly reshaping undergraduate mathematics instruction, posing challenges to teaching, assessment, and academic integrity amid limited institutional guidance. This mixed-methods study examined undergraduate mathematics faculty attitudes toward GenAI integration (N = 41) using the technology acceptance model (TAM) and will-skill-tool (WST) frameworks. Faculty showed moderate openness/curiosity (M = 3.46), low confidence (M = 2.85), strong institutional support needs (M = 3.86), and minimal teaching influence (M = 2.95). Student impact concerns correlated with openness/curiosity (r = .33, p < .05) and curriculum modification willingness (r = .45, p < .01). Multiple regression revealed openness/curiosity as the only significant predictor of professional practice influence (β = .50, p = .013, R² = .41), challenging TAM's emphasis on perceived ease of use. Despite low confidence, 73.9% modified their teaching. Findings reveal incomplete WST implementation, underscoring institutional needs for support systems enabling responsible GenAI integration.

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

EURASIA J Math Sci Tech Ed, Volume 22, Issue 4, April 2026, Article No: em2804

https://doi.org/10.29333/ejmste/18126

Publication date: 01 Apr 2026

Online publication date: 15 Mar 2026

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Article Downloads: 18

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