Aceptación y uso de inteligencia artificial en estudiantes de educación superior: una revisión sistemática
DOI:
https://doi.org/10.64973/7mtywj81Palabras clave:
inteligencia artificial, educación superior, aceptación de tecnología, estudiantes universitarios, inteligencia artificial generativa, ChatGPTResumen
La incorporación acelerada de herramientas de inteligencia artificial (IA), especialmente sistemas generativos y chatbots, ha transformado las prácticas de búsqueda, escritura, estudio y resolución de tareas en la educación superior. Este estudio analizó la evidencia científica publicada entre 2022 y 2026 sobre los factores asociados con la aceptación, intención de uso y utilización efectiva de herramientas de IA por estudiantes universitarios. Se realizó una revisión sistemática conforme a PRISMA 2020, considerando estudios indexados en Scopus, Web of Science Core Collection y ERIC, publicados en español, inglés o portugués. Se incluyeron investigaciones que evaluaron aceptación, adopción, intención conductual o uso de IA mediante modelos como TAM, UTAUT, UTAUT2 y extensiones afines. Los resultados muestran que la utilidad percibida, el hábito, la confianza, la actitud, la facilidad de uso, la influencia social y las condiciones facilitadoras favorecen la adopción. En contraste, el riesgo percibido, las preocupaciones sobre integridad académica y la ausencia de políticas claras actúan como barreras o moderadores. La relevancia de estos factores varía según el país, la experiencia previa y la finalidad académica. Se concluye que la aceptación de la IA es multidimensional y requiere alfabetización, regulación institucional y un uso crítico, transparente y formativo.
Referencias
Baig, M. I., & Yadegaridehkordi, E. (2024). ChatGPT in the higher education: A systematic literature review and research challenges. International Journal of Educational Research, 127, 102411. https://doi.org/10.1016/j.ijer.2024.102411
Bearman, M., Ryan, J., & Ajjawi, R. (2023). Discourses of artificial intelligence in higher education: A critical literature review. Higher Education, 86, 369–385. https://doi.org/10.1007/s10734-022-00937-2
Bouteraa, M., Bin-Nashwan, S. A., Al-Daihani, M., Dirie, K. A., Benlahcene, A., Sadallah, M., Zaki, H. O., Lada, S., Ansar, R., Fook, L. M., & Chekima, B. (2024). Understanding the diffusion of AI-generative (ChatGPT) in higher education: Does students’ integrity matter? Computers in Human Behavior Reports, 14, 100402. https://doi.org/10.1016/j.chbr.2024.100402
Duong, C. D., Vu, T. N., & Ngo, T. V. N. (2023). Applying a modified technology acceptance model to explain higher education students’ usage of ChatGPT: A serial multiple mediation model with knowledge sharing as a moderator. The International Journal of Management Education, 21(3), 100883. https://doi.org/10.1016/j.ijme.2023.100883
Espinoza-Bravo, M. G., Cabezas-Cabezas, R., Perez-Cepeda, M., Carvache-Franco, O., & Carvache-Franco, W. (2025). AIDUA (artificial intelligence device use and acceptance) model to assess the acceptance of AI in the learning practices of higher education students. Cogent Education, 12(1), 2560618. https://doi.org/10.1080/2331186X.2025.2560618
Faraon, M., Rönkkö, K., Milrad, M., & Tsui, E. (2025). International perspectives on artificial intelligence in higher education: An explorative study of students’ intention to use ChatGPT across the Nordic countries and the USA. Education and Information Technologies, 30(13), 17835–17880. https://doi.org/10.1007/s10639-025-13492-x
Foroughi, B., Senali, M. G., Iranmanesh, M., Khanfar, A., Ghobakhloo, M., Annamalai, N., & Naghmeh-Abbaspour, B. (2024). Determinants of intention to use ChatGPT for educational purposes: Findings from PLS-SEM and fsQCA. International Journal of Human–Computer Interaction, 40(17), 4501–4520. https://doi.org/10.1080/10447318.2023.2226495
George-Reyes, C. E., Mérida-Córdova, E. J., Yeguas-Bolivar, E., & Monzalvo-Serrano, L. (2026). Artificial intelligence acceptance in higher education: Perceptions from Mexico, Spain, and Finland. Information, 17(6), 575. https://doi.org/10.3390/info17060575
Grassini, S., Aasen, M. L., & Møgelvang, A. (2024). Understanding university students’ acceptance of ChatGPT: Insights from the UTAUT2 model. Applied Artificial Intelligence, 38(1), 2371168. https://doi.org/10.1080/08839514.2024.2371168
Habibi, A., Muhaimin, M., Danibao, B. K., Wibowo, Y. G., Wahyuni, S., & Octavia, A. (2023). ChatGPT in higher education learning: Acceptance and use. Computers and Education: Artificial Intelligence, 5, 100190. https://doi.org/10.1016/j.caeai.2023.100190
Howlader, M. H., Tohan, M. M., Zaman, S., Chanda, S. K., Jiaxin, G., & Rahman, M. A. (2025). Factors influencing the acceptance and usage of ChatGPT as an emerging learning tool among higher education students in Bangladesh: A structural equation modeling. Cogent Education, 12(1), 2504224. https://doi.org/10.1080/2331186X.2025.2504224
Johnston, H., Wells, R. F., Shanks, E. M., Boey, T., & Parsons, B. N. (2024). Student perspectives on the use of generative artificial intelligence technologies in higher education. International Journal for Educational Integrity, 20, 2. https://doi.org/10.1007/s40979-024-00149-4
Lai, C. Y., Cheung, K. Y., Chan, C. S., & Law, K. K. (2024). Integrating the adapted UTAUT model with moral obligation, trust and perceived risk to predict ChatGPT adoption for assessment support: A survey with students. Computers and Education: Artificial Intelligence, 6, 100246. https://doi.org/10.1016/j.caeai.2024.100246
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
Parveen, K., Phuc, T. Q. B., Alghamdi, A. A., Hajjej, F., Obidallah, W. J., Alduraywish, Y. A., & Shafiq, M. (2024). Unraveling the dynamics of ChatGPT adoption and utilization through Structural Equation Modeling. Scientific Reports, 14, 23469. https://doi.org/10.1038/s41598-024-74406-4
Polyportis, A., & Pahos, N. (2025). Understanding students’ adoption of the ChatGPT chatbot in higher education: The role of anthropomorphism, trust, design novelty and institutional policy. Behaviour & Information Technology, 44(2), 315–336. https://doi.org/10.1080/0144929X.2024.2317364
Raffaghelli, J. E., Rodríguez, M. E., Guerrero-Roldán, A.-E., & Bañeres, D. (2022). Applying the UTAUT model to explain the students’ acceptance of an early warning system in Higher Education. Computers & Education, 182, 104468. https://doi.org/10.1016/j.compedu.2022.104468
Salas-Pilco, S. Z., & Yang, Y. (2022). Artificial intelligence applications in Latin American higher education: A systematic review. International Journal of Educational Technology in Higher Education, 19, 21. https://doi.org/10.1186/s41239-022-00326-w
Salhab, R., & Aboushi, M. M. (2025). Influence of AI literacy and 21st-century skills on the acceptance of generative artificial intelligence among college students. Frontiers in Education, 10, 1640212. https://doi.org/10.3389/feduc.2025.1640212
Shahzad, M. F., Xu, S., & Javed, I. (2024). ChatGPT awareness, acceptance, and adoption in higher education: The role of trust as a cornerstone. International Journal of Educational Technology in Higher Education, 21, 46. https://doi.org/10.1186/s41239-024-00478-x
Strzelecki, A. (2024). Students’ acceptance of ChatGPT in higher education: An extended unified theory of acceptance and use of technology. Innovative Higher Education, 49, 223–245. https://doi.org/10.1007/s10755-023-09686-1
Strzelecki, A., & ElArabawy, S. (2024). Investigation of the moderation effect of gender and study level on the acceptance and use of generative AI by higher education students: Comparative evidence from Poland and Egypt. British Journal of Educational Technology, 55(3), 1209–1230. https://doi.org/10.1111/bjet.13425
Wu, W., Zhang, B., Li, S., & Liu, H. (2022). Exploring factors of the willingness to accept AI-assisted learning environments: An empirical investigation based on the UTAUT model and perceived risk theory. Frontiers in Psychology, 13, 870777. https://doi.org/10.3389/fpsyg.2022.870777
Zou, M., & Huang, L. (2023). To use or not to use? Understanding doctoral students’ acceptance of ChatGPT in writing through technology acceptance model. Frontiers in Psychology, 14, 1259531. https://doi.org/10.3389/fpsyg.2023.1259531
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