Percepción del aprendizaje de los alumnos universitarios con el uso de herramientas de inteligencia artificial

Cristina Gallego-Gomez; Eduardo Carlos Dittmar

doi:10.31637/epsir-2026-2042

Authors

Cristina Gallego-Gomez Universidad Rey Juan Carlos https://orcid.org/0000-0002-7477-520X
Eduardo Carlos Dittmar Universidad Rey Juan Carlos https://orcid.org/0000-0002-8087-2444

DOI:

https://doi.org/10.31637/epsir-2026-2042

Keywords:

perception, artificial intelligence, students, university students, technology, learning, digital tools, use

Abstract

Introduction: In recent years, artificial intelligence (AI) tools have begun to be significantly integrated into the educational field, transforming the way university students access knowledge and develop key competencies. This article analyzes university students' perceptions of their learning when using these tools, addressing the factors of the UTAUT model. Methodology: Based on a literature review and a survey of 108 undergraduate students, the main conclusions are drawn regarding the use and perceptions of ease of using AI for their academic work. Results: The bibliometric analysis shows that there is an increase in literature in this field; through a co-occurrence analysis, the themes are identified. Additionally, a use greater than 90% in the use of AI is detected, specifically using GPT Chat as a tool due to the perception of ease, social utility, and accessibility of the resource. Discussion: The differences observed confirm the results obtained in previous studies and highlight the need for digital literacy in the face of learning challenges. Conclusions: Most students perceive that AI tools significantly improve their learning experience.

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Author Biographies

Cristina Gallego-Gomez, Universidad Rey Juan Carlos

PhD in Business Organisation from Rey Juan Carlos University, obtaining the first extraordinary doctoral award. ANECA-accredited lecturer, she currently teaches at Rey Juan Carlos University, where she is part of the OpenInnova high-performance research group. She is a postdoctoral researcher at the University of Porto. She has taught at Carlos III University in Madrid, the University of the Americas, ESIC University, among others.

Eduardo Carlos Dittmar, Universidad Rey Juan Carlos

Economist and Doctor of Economics and Business Studies. He brings extensive teaching experience at both undergraduate and postgraduate levels. His academic work encompasses fundamental and applied research, which has resulted in more than 50 peer-reviewed publications and book chapters. Throughout his career, he has been actively involved in various research groups and has served on the editorial boards of numerous academic journals. His research interests focus on new technologies, corporate social responsibility, strategic marketing and business ethics.

References

Araya-Guzmán, S., Riffo-Rodríguez, E. y Salazar-Concha, C. (2023). Incidencia de la expectativa de esfuerzo y la expectativa de desempeño en la satisfacción laboral y compromiso organizativo de usuarios de plataformas digitales. Revista Ibérica de Sistemas e Tecnologias de Informação, 57, 166-176. https://acortar.link/17RU12

Aparicio, W. (2023). La Inteligencia Artificial y su Incidencia en la Educación: Transformando el Aprendizaje para el Siglo XXI. Revista Internacional De Pedagogía E Innovación Educativa, 3(2), 217-230. https://doi.org/10.51660/ripie.v3i2.133 DOI: https://doi.org/10.51660/ripie.v3i2.133

Alegre Ortiz, J., Cuevas Gutiérrez, I. y Mendoza Vargas, M. (2022). Aceptación y uso de la tecnología en profesores universitarios. Vinculatégica EFAN, 7(2), 84-93. https://doi.org/10.29105/vtga7.1-86 DOI: https://doi.org/10.29105/vtga7.1-86

Barac, M. y López-Rodríguez, M. I. (2024). ¿Cómo integra el estudiantado universitario la IA en sus procesos de aprendizaje? European Public & Social Innovation Review, 9, 1-14. https://doi.org/10.31637/epsir-2024-707 DOI: https://doi.org/10.31637/epsir-2024-707

Collie, R., Martin, A. y Gasevic, D. (2024). Teachers’ generative AI self-efficacy, valuing, and integration at work: Examining job resources and demands. Computers and Education: Artificial Intelligence, 7. https://doi.org/10.1016/j.caeai.2024.100333 DOI: https://doi.org/10.1016/j.caeai.2024.100333

Crompton, H. y Burke, D. (2023). Inteligencia artificial en la educación superior: el estado actual del campo. Int J Educ Technol High Educ, 20, 22. DOI: https://doi.org/10.1186/s41239-023-00392-8

https:/doi.org/10.1186/s41239-023-00392-8

Deci, E. y Ryan, R. (1985). The general causality orientations scale: Self-determination in personality. Journal of research in personality, 19(2), 109-134.

https://doi.org/10.1016/0092-6566(85)90023-6 DOI: https://doi.org/10.1016/0092-6566(85)90023-6

Espejo Aubá, P. C. (2024). La Inteligencia Artificial en educación: percepciones y saberes de los docentes. European Public & Social Innovation Review, 9, 1-19. https://doi.org/10.31637/epsir-2024-898 DOI: https://doi.org/10.31637/epsir-2024-898

Flores-Vivar, J. y García-Peñalvo, F. (2023). Reflections on the ethics, potential, and challenges of artificial intelligence in the framework of quality education (SDG4). [Reflexiones sobre la ética, potencialidades y retos de la Inteligencia Artificial en el marco de la Educación de Calidad (ODS4)]. Comunicar, 74, 37-47. https://doi.org/10.3916/C74-2023-03 DOI: https://doi.org/10.3916/C74-2023-03

Gan, C. L., Bong, Y. H., Goh, G. G. G. y Liew, T. W. (2025). Supporting student-centred learning with mobile technology: UTAUT and Hofstede’s dimensions of culture / Apoyo al aprendizaje centrado en el alumno mediante la tecnología móvil: la UTAUT y las dimensiones culturales de Hofstede. Culture and Education, 0(0). https://doi.org/10.1177/11356405251316068 DOI: https://doi.org/10.1177/11356405251316068

Gallego Gómez, C., Tapia López, A. y Márquez García, J. A. (2024). Factores que determinan el uso de las redes sociales como plataformas de información en la Generación Z. ESIC Market. Economics and Business Journal, 55(2). https://10.7200/esicm.55.359 DOI: https://doi.org/10.7200/esicm.55.359

Gallent-Torres, C., Arenas-Romero,B., Vallespir-Adillón, M. y Foltýnek, T. (2024). Inteligencia Artificial en educación: entre riesgos y potencialidades. Práxis Educativa, 19, 1-29. https://10.5212/PraxEduc.v.19.23760.083 DOI: https://doi.org/10.5212/PraxEduc.v.19.23760.083

Guo, Q. y Xu, Y. (2024). Student teachers’ motivation to teach: The roles of basic psychological needs, teaching self-efficacy, and teaching emotions from a variable-and person-centered approach. Teaching and Teacher Education, 148. https://doi.org/10.1016/j.tate.2024.104688 DOI: https://doi.org/10.1016/j.tate.2024.104688

Hernández Camblor, C. y Moral Jiménez, M. V. (2024). Uso de las redes sociales virtuales y su relación con la percepción de soledad y las habilidades sociales en jóvenes adultos españoles de la generación Z y la generación Y. Acta Colombiana de Psicología, 27(1), 229-245. https://doi.org/10.14718/ACP.2024.27.1.13 DOI: https://doi.org/10.14718/ACP.2024.27.1.13

Luckin, R., Holmes, W., Griffiths, M. y Forcier, L. B. (2016). Intelligence Unleashed. An argument for AI in Education. London: Pearson.

Martín García, A. V., García del Dujo, Á. y Muñoz Rodríguez, J. M. (2014). Factores determinantes de adopción de blended learning en educación superior. Adaptación del modelo UTAUT. Educación XX1, 17(2), 217-240. https://doi.org/10.5944/educxx1.17.2.11489 DOI: https://doi.org/10.5944/educxx1.17.2.11489

Mishra, V. y Mishra, M. P. (2023). “PRISMA for Review of Management Literature – Method, Merits, and Limitations – An Academic Review”. En S. Rana, J. Singh and S. Kathuria S. (Eds.), Advancing Methodologies of Conducting Literature Review in Management Domain (pp. 125-136) Emerald Publishing Limited, Leeds.

https://doi.org/10.1108/S2754-586520230000002007 DOI: https://doi.org/10.1108/S2754-586520230000002007

Piaget, J. (1952). Origins of Intelligence in Children. New York: International Universities Press. DOI: https://doi.org/10.1037/11494-000

Ricardo Cabrera, H., Rodríguez Pérez, B., León González, J. L. y Medina León, A. (2021). Bases y oportunidades de la vinculación universidad-empresa. Revista Universidad y Sociedad, 13(1), 300-306. https://acortar.link/WCxX6p

Romero-Rodríguez, J. M., Ramírez-Montoya, M. S. y Buenestado-Fernández, M. (2023). Use of ChatGPT at University as a Tool for Complex Thinking: Students’ Perceived Usefulness. Journal of New Approaches in Educational Research, 12, 323-339. https://doi.org/10.7821/naer.2023.7.1458 DOI: https://doi.org/10.7821/naer.2023.7.1458

Romo Padilla, G., Rubio Caicedo, C., Gómez Rodríguez, V. y Nivel Cornejo, M. (2023). Herramientas digitales en el proceso enseñanza-aprendizaje mediante revisión bibliográfica. Polo del Conocimiento, 8(10), 313-344. https://doi.org/10.23857/pc.v8i10.6127

Sosa-Calero, S. M., Mendoza-Loor, J. J., Araujo-Sandoval, O. I. y Choez-Calderón, C. J. (2023). Educación y TIC’s: herramientas y estrategias para un aprendizaje efectivo. Código Científico Revista De Investigación, 4, 1380-1404. https://doi.org/10.55813/gaea/ccri/v4/nE2/224 DOI: https://doi.org/10.55813/gaea/ccri/v4/nE2/224

Strzelecki, A. (2024) Aceptación de ChatGPT por parte de los estudiantes en la educación superior: Una teoría unificada extendida de la aceptación y el uso de la tecnología. Innovative Higher Education, 49, 223-245.

https://doi.org/10.1007/s10755-023-09686-1 DOI: https://doi.org/10.1007/s10755-023-09686-1

Venkatesh, V., Morris, M. G., Davis, F. D. y Davis, G. B. (2003). User acceptance of information technology: towards a unified view. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540 DOI: https://doi.org/10.2307/30036540

Venkatesh, V., Thong, J. Y. L. y Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157-178. https://doi.org/10.2307/41410412 DOI: https://doi.org/10.2307/41410412

Vygotsky, L. S. (1978). Mind and society: The development of higher psychological processes. Harvard University Press.