Inteligencia artificial generativa, pensamiento crítico e integridad académica en la evaluación universitaria
DOI:
https://doi.org/10.59169/pentaciencias.v8i3.1891Palabras clave:
inteligencia artificial generativa; educación superior; evaluación; pensamiento crítico; integridad académicaResumen
La expansión de la inteligencia artificial generativa ha modificado las condiciones bajo las cuales las universidades interpretan la autoría, el aprendizaje y la evidencia evaluativa. El objetivo de este artículo es analizar críticamente sus implicaciones para el pensamiento crítico, la integridad académica y la evaluación en educación superior, y proponer criterios para su integración responsable. Se realizó una revisión documental crítica e integrativa de literatura científica y documentos institucionales publicados principalmente entre 2021 y 2026. Los resultados muestran que los efectos educativos dependen del diseño de las tareas, la alfabetización de docentes y estudiantes, la transparencia de uso y la capacidad de verificar el proceso intelectual. Las estrategias centradas exclusivamente en prohibición y detección resultan insuficientes. Como contribución conceptual se propone el Marco EVALUAR-IA, compuesto por siete dimensiones: evidencia del proceso, verificación, autoría demostrable, lectura crítica, uso ético, aprendizaje reflexivo y responsabilidad humana. Se concluye que la evaluación universitaria debe desplazarse del producto final hacia la comprensión, la justificación, la verificación y la trazabilidad del razonamiento.
Descargas
Citas
Bittle, K., & El-Gayar, O. (2025). Generative AI and academic integrity in higher education: A systematic review and research agenda. Information, 16(4), 296. https://doi.org/10.3390/info16040296
Chan, C. K. Y. (2023). A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, 20, 38. https://doi.org/10.1186/s41239-023-00408-3
Cong-Lem, N., & Thuy-Dung, N. T. (2026). Towards a framework for understanding and assessing critical thinking in generative AI-enhanced learning environments: A scoping review. European Journal of Psychology of Education, 41(2), Article 41. https://doi.org/10.1007/s10212-026-01089-y
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 61(2), 228–239. https://doi.org/10.1080/14703297.2023.2190148
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi, M. A., Al-Busaidi, A. S., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., … Wright, R. (2023). “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642
Farrokhnia, M., Banihashemi, S. K., Noroozi, O., & Wals, A. (2024). A SWOT analysis of ChatGPT: Implications for educational practice and research. Innovations in Education and Teaching International, 61(3), 460–474. https://doi.org/10.1080/14703297.2023.2195846
Helal, M. Y. I., Elgendy, I. A., Albashrawi, M. A., Dwivedi, Y. K., Al-Ahmadi, M. S., & Jeon, I. (2025). The impact of generative AI on critical thinking skills: A systematic review, conceptual framework and future research directions. Information Discovery and Delivery. https://doi.org/10.1108/IDD-05-2025-0125
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., … Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
Lo, C. K. (2023). What is the impact of ChatGPT on education? A rapid review of the literature. Education Sciences, 13(4), 410. https://doi.org/10.3390/educsci13040410
Miao, F., & Cukurova, M. (2024). AI competency framework for teachers. UNESCO. https://doi.org/10.54675/ZJTE2084
Miao, F., & Holmes, W. (2023). Guidance for generative AI in education and research. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000386693
Miao, F., Shiohira, K., & Lao, N. (2024). AI competency framework for students. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000391105
Moorhouse, B. L., Yeo, M. A., & Wan, Y. W. (2023). Generative AI tools and assessment: Guidelines of the world’s top-ranking universities. Computers and Education Open, 5, 100151. https://doi.org/10.1016/j.caeo.2023.100151
Ng, D. T. K., Leung, J. K. L., Chu, K. W. S., & Qiao, M. S. (2021). AI literacy: Definition, teaching, evaluation and ethical issues. Proceedings of the Association for Information Science and Technology, 58(1), 504–509. https://doi.org/10.1002/pra2.487
Nikolic, S., Daniel, S., Haque, R., Belkina, M., Hassan, G. M., Grundy, S., Lyden, S., Neal, P., & Sandison, C. (2023). ChatGPT versus engineering education assessment: A multidisciplinary and multi-institutional benchmarking and analysis of this generative artificial intelligence tool to investigate assessment integrity. European Journal of Engineering Education, 48(4), 559–614. https://doi.org/10.1080/03043797.2023.2213169
Overono, A. L., & Ditta, A. S. (2023). The rise of artificial intelligence: A clarion call for higher education to redefine learning and reimagine assessment. College Teaching, 73(2), 123–126. https://doi.org/10.1080/87567555.2023.2233653
Perkins, M. (2023). Academic integrity considerations of AI large language models in the post-pandemic era: ChatGPT and beyond. Journal of University Teaching & Learning Practice, 20(2), Article 7. https://doi.org/10.53761/1.20.02.07
Rudolph, J., Tan, S., & Tan, S. (2023). ChatGPT: Bullshit spewer or the end of traditional assessments in higher education? Journal of Applied Learning & Teaching, 6(1), 342–363. https://doi.org/10.37074/jalt.2023.6.1.9
Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023). What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart Learning Environments, 10, 15. https://doi.org/10.1186/s40561-023-00237-x
Xia, Q., Weng, X., Ouyang, F., Lin, T. J., & Chiu, T. K. F. (2024). A scoping review on how generative artificial intelligence transforms assessment in higher education. International Journal of Educational Technology in Higher Education, 21, 40. https://doi.org/10.1186/s41239-024-00468-z
Publicado
Cómo citar
Número
Sección
Licencia
Derechos de autor 2026 Revista Científica Arbitrada Multidisciplinaria PENTACIENCIAS
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.
