Understanding students’ perceptions of generative AI: Implications for pedagogy and graduate employability

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Significant predictors of generative AI use include perceived usefulness and ease of use.
Personal innovativeness showed strong correlations with the technology acceptance model variables.
Gender and field of study influenced adoption, with males and economics students using generative AI more.
Tailored teaching strategies are necessary to enhance student engagement and readiness for AI-driven careers.

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Survey examines factors influencing student engagement with generative AI, highlighting the role of technology acceptance and demographics.

Rispler et al. (2025) studied this question.

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Survey examines factors influencing student engagement with generative AI, highlighting the role of technology acceptance and demographics.