Vol. 72 No. 1 (2026): Tecnologías emergentes y sociedad
Articles

Methodological proposal to analyze the acceptance, use, and integration of generative artificial intelligence in higher education institutions

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  • María de Lourdes Flores Portillo ,
  • Juan D. Machin-Mastromatteo,
  • Javier Tarango
María de Lourdes Flores Portillo
Universidad Autónoma de Chihuahua
Bio
Juan D. Machin-Mastromatteo
Universidad Autónoma de Chihuahua
Bio
Javier Tarango
Universidad Autónoma de Chihuahua
Bio

Published — Updated on 2026-01-07

Keywords

  • generative artificial intelligence,
  • methodological proposal,
  • higher education,
  • UTAUT model,
  • technology adoption,
  • artificial intelligence ethics
    • ...More
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Copyright (c) 2025 AULA Revista de Humanidades y Ciencias Sociales

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How to Cite

Flores Portillo , M. de L., Machin-Mastromatteo, J. D., & Tarango, J. (2026). Methodological proposal to analyze the acceptance, use, and integration of generative artificial intelligence in higher education institutions. AULA Revista De Humanidades Y Ciencias Sociales, 72(1). https://doi.org/10.33413/aulahcs.2026.72i1.450

Abstract

This article presents a methodological proposal to study the adoption, acceptance, and integration of generative artificial intelligence (AI) in higher education institutions, derived from an analysis of specialized literature and encompassing seven dimensions of analysis: (1) moderating factors; (2) challenges and barriers to the integration of AI in teaching and learning processes; (3) performance expectancy; (4) effort expectancy; (5) social influence; (6) facilitating conditions; and (7) ethical implications. The proposal is based on the Unified Theory of Acceptance and Use of Technology (UTAUT) and follows a sequential explanatory mixed-methods design that combines a quantitative phase, which includes a validated questionnaire, and a qualitative phase focused on conducting in-depth interviews. This approach seeks to identify the factors that influence the intention to use and the effective adoption of AI, as well as the perceptions, resistances, and contextual conditions that affect technological integration processes. Finally, this article concludes with the presentation of selected findings reported in specialized literature on the use and implementation of AI in higher education contexts, aiming to synthesize the trends identified by other researchers in similar studies regarding the seven dimensions of analysis presented in this article. In this way, the proposal offers a methodological framework adaptable to different higher education institutions, designed to promote reflective and evidence-based studies about AI in education.

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