Undergraduate mathematics faculty attitudes and experiences with generative AI integration

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 (<i>N</i> = 41) using the technology acceptance model (TAM) and will-skill-tool (WST) frameworks. Faculty showed moderate openness/curiosity (<i>M</i> = 3.46), low confidence (<i>M</i> = 2.85), strong institutional support needs (<i>M</i> = 3.86), and minimal teaching influence (<i>M</i> = 2.95). Student impact concerns correlated with openness/curiosity (<i>r</i> = .33, <i>p</i> < .05) and curriculum modification willingness (<i>r</i> = .45, <i>p</i> < .01). Multiple regression revealed openness/curiosity as the only significant predictor of professional practice influence (β = .50, <i>p</i> = .013, <i>R</i>² = .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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