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September 10, 2025Journal of Teaching and Learning for Graduate EmployabilityOpen Access

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

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Authors

CRClara RisplerMMMichal Mashiach‐EizenbergGYGila Yakov

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Overview

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

Key Points

  • 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.

Cite This Study

Rispler et al. (2025) studied this question.

synapsesocial.com/papers/68c1d9a154b1d3bfb60fbb9dhttps://doi.org/10.21153/jtlge2025vol16no1art2084
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Exploring the Mechanisms Influencing Graduate Students’ Adoption of Generative AI: Insights from the Technology Acceptance Model2026
  2. 2Generative artificial intelligence in higher education: Students’ journey through opportunities, challenges, and the horizons of academic transformation2025
  3. 3Generative-AI, a Learning Assistant? Factors Influencing Higher-Ed Students' Technology Acceptance2024 · 108 citations
  4. 4Acceptance and Usage Patterns of Generative Artificial Intelligence Among Higher Education Students2026
  5. 5Perceptions and Paradoxes: Exploring Graduate Students' Attitudes towards Generative AI's Role in Higher Education2025