Gen-AI Tools in Academia: A Cluster Analysis of University Faculty Adoption
Submitted: 2025-05-08
|Accepted: 2025-08-27
|Published: 2025-10-20
Copyright (c) 2025 Antonio Chamorro-Mera, Francisco Javier Miranda-González
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
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Keywords:
Artificial Intelligence, Perceived Usefulness, Perceived Ease of Use, Subjective Norm, Higher Education Institutions
Supporting agencies:
Abstract:
Generative artificial intelligence (Gen-AI) has arrived to revolutionize many human activities, including teaching and learning processes. Teachers in higher education can and should ethically, legally, and accurately incorporate this new technology into their teaching, especially since the younger generation of students has integrated it into their daily lives practically since the launch of ChatGPT and uses it as a new learning medium. In this context, this research aims to analyse the short-term penetration potential of Gen-AI in the teaching activities of Spanish university teachers, identifying segments of teachers with different beliefs and attitudes towards this technology.
Specifically, three segments have been identified. The largest segment consists of teachers who are still undecided about the application of Gen-AI in their teaching activities, as they are not yet clear about its practical utility and do not have confidence in its accuracy and quality. At one end of these undecided teachers is another group classified as sceptics, who do not use these tools due to a very low perceived utility, although they have a high perception of ease of use and do not perceive high risks from their use. On the opposite end are the explorer teachers who are pioneers in its use, trusting both the utility and the current accuracy and quality of the results generated by these tools. If university administrators want to promote the use of artificial intelligence among their academics, they will need to design different strategies and actions for each segment.
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