Acceptance of generative artificial intelligence among teachers: adaptation and validation of an instrument based on the TAM

Authors

  • Jose Gabriel Rodríguez-Rivas Tecnologico Nacional de Mexico Campus Instituto tecnologico de Durango https://orcid.org/0000-0002-7031-5097
  • Fernando Ayala-Partida Tecnológico Nacional de México / Instituto Tecnológico de Durango
  • Luis Campa-Galindo Tecnológico Nacional de México / Instituto Tecnológico de Durango

DOI:

https://doi.org/10.51247/pdlc.v6i2.766

Keywords:

Generative artificial intelligence, higher education, faculty, Technology Acceptance Model, instrument validation.

Abstract

Generative artificial intelligence (GAI) represents a disruptive tool in higher education, with significant potential to transform teaching, research, and academic management. The objective of this study was to adapt and validate a reliable and valid instrument to assess the acceptance and use of GAI among higher education faculty, based on the Technology Acceptance Model (TAM). A quantitative, non-experimental, cross-sectional study with an instrumental approach was conducted with a sample of 100 faculty members. The instrument, called the Generative Artificial Intelligence Acceptance and Use Scale (EAU-IAG), was subjected to exploratory and confirmatory factor analyses. The EFA identified a four-factor structure consistent with the TAM, explaining 63.96% of the total variance. The CFA confirmed the factorial validity of the proposed model, showing adequate and statistically significant standardized factor loadings, as well as satisfactory global fit indices (CFI = 0.969, TLI = 0.964, RMSEA = 0.039). In addition, reliability coefficients indicated high internal consistency across dimensions. These findings support the use of the EAU-IAG as a valid and reliable instrument for diagnostic studies and future research on the adoption of GAI in higher education contexts.

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References

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Published

2026-04-01

How to Cite

Acceptance of generative artificial intelligence among teachers: adaptation and validation of an instrument based on the TAM. (2026). Science Portal, 6(2), 217-232. https://doi.org/10.51247/pdlc.v6i2.766

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