Herramientas de inteligencia artificial generativa para el aprendizaje: Una revisión sistemática
Generative Artificial Intelligence Tools for Learning: A Systematic Review ArticleBarra lateral del artículo
Contenido principal del artículo
Contexto: La inteligencia artificial generativa ha transformado los ecosistemas educativos actuales, lo que lleva a cuestionar cuáles son sus verdaderos efectos en el aprendizaje de los estudiantes. Objetivo: Analizar las implicaciones de las herramientas de inteligencia artificial generativa para el aprendizaje de los estudiantes de distintos niveles educativos y contextos geográficos. Metodología: Se realizó una revisión sistemática basada en el método PRISMA, donde se identificaron 25 estudios publicados de enero del 2022 a marzo del 2026. Resultados: ChatGPT resultó ser la plataforma más utilizada, lo que destaca su accesibilidad y versatilidad. Las implicaciones educativas presentan una dualidad pues, por un lado, se observan beneficios como la personalización del aprendizaje, el aumento de la motivación y la mejora en la eficiencia académica; y por el otro, existen riesgos como la dependencia tecnológica, la disminución del pensamiento crítico y dilemas éticos. Los estudios experimentales muestran mejoras en el rendimiento académico cuando se combina con estrategias pedagógicas bien estructuradas. Las investigaciones correlacionales reflejan que la calidad de la interacción con estas herramientas puede predecir logros académicos más altos, aunque el uso excesivo o mecánico tiende a relacionarse con resultados más bajos. Conclusión: La efectividad de la inteligencia artificial generativa no radica solo en sus capacidades técnicas, sino en cómo se integra con marcos pedagógicos bien pensados, la supervisión de los docentes y el desarrollo de la alfabetización digital.
Background: Generative artificial intelligence has transformed current educational ecosystems, leading to questions about its true effects on student learning. Objective: To analyze the implications of generative artificial intelligence tools for student learning across different educational levels and geographical contexts. Methodology: A systematic review based on the PRISMA method was conducted, identifying 25 studies published between January 2022 and March 2026. Results: ChatGPT emerged as the most widely used platform, highlighting its accessibility and versatility. The educational implications present a duality: on the one hand, benefits such as personalized learning, increased motivation, and improved academic efficiency are observed; on the other hand, risks such as technological dependence, decreased critical thinking, and ethical dilemmas exist. Experimental studies show improvements in academic performance when combined with well-structured pedagogical strategies. Correlational studies show that the quality of interaction with these tools can predict higher academic achievement, although excessive or rote use tends to be associated with lower results. Conclusion: The effectiveness of generative artificial intelligence lies not only in its technical capabilities, but also in how it is integrated with well-designed pedagogical frameworks, teacher supervision, and the development of digital literacy.
Descargas
Detalles del artículo
Bai, Y. y Wang, S. (2025). Impact of generative AI interaction and output quality on university students’ learning outcomes: A technology-mediated and motivation-driven approach. Scientific Reports, 15(1), 24054. https://doi.org/10.1038/s41598-025-08697-6
Baidoo, D., Asamoah, D., Amoako, I. y Mahama, I. (2024). Exploring student perspectives on generative artificial intelligence in higher education learning. Discover Education, 3(1), 98. https://doi.org/10.1007/s44217-024-00173-z
Bell, R. y Bell, H. (2023). Entrepreneurship education in the era of generative artificial intelligence. Entrepreneurship Education, 6(3), 229-244. https://doi.org/10.1007/s41959-023-00099-x
Celik, I., Dindar, M., Muukkonen, H. y Järvelä, S. (2022). The Promises and Challenges of Artificial Intelligence for Teachers: A Systematic Review of Research. TechTrends, 66(4), 616-630. https://doi.org/10.1007/s11528-022-00715-y
Chen, B., Zhu, X. y Castillo, F. D. del. (2023). Integrating generative AI in knowledge building. Computers and Education: Artificial Intelligence, 5, 100184. https://doi.org/10.1016/j.caeai.2023.100184
Dawson, M. G., Deer, R. y Boguslawski, S. (2025). Cognitive dissonance in programming education: A qualitative exploration of the impact of generative AI on application-directed learning. Computers in Human Behavior Reports, 19, 100724. https://doi.org/10.1016/j.chbr.2025.100724
Fan, L., Deng, K. y Liu, F. (2025). Educational impacts of generative artificial intelligence on learning and performance of engineering students in China. Scientific Reports, 15(1), 26521. https://doi.org/10.1038/s41598-025-06930-w
Giannakos, M., Azevedo, R., Brusilovsky, P., Cukurova, M., Dimitriadis, Y., Hernandez, D., Järvelä, S., Mavrikis, M. y Rienties, B. (2025). The promise and challenges of generative AI in education. Behaviour & Information Technology, 44(11), 2518-2544. https://doi.org/10.1080/0144929X.2024.2394886
Grassini, S. (2023). Shaping the Future of Education: Exploring the Potential and Consequences of AI and ChatGPT in Educational Settings. Education Sciences, 13(7), 692. https://doi.org/10.3390/educsci13070692
Hon, K. (2026). Generative AI in Higher Education: A Systematic Review of Its Effects on Learning Outcomes and Academic Performance. Journal of Educational Technology Systems, 54(3), 537-560. https://doi.org/10.1177/00472395251400089
Hou, C., Zhu, G., Liu, Y., Sudarshan, V., Chong, J. L. L., Zhang, F. Y., Tan, M. Y. H. y Ong,
Y. S. (2026). The effects of critical thinking intervention on reliance behaviors, problem-solving quality, and creativity during human-Generative AI collaborative learning. Computers & Education, 247, 105576. https://doi.org/10.1016/j.compedu.2026.105576
Jauhiainen, J. S. y Guerra, A. G. (2023). Generative AI and ChatGPT in School Children’s Education: Evidence from a School Lesson. Sustainability, 15(18), 14025. https://doi.org/10.3390/su151814025
Jošt, G., Taneski, V. y Karakatič, S. (2024). The Impact of Large Language Models on Programming Education and Student Learning Outcomes. Applied Sciences, 14(10). https://doi.org/10.3390/app14104115
Kangwa, D., Msafiri, M. y Zhang, W. (2025). Can Generative AI Revolutionise Academic Skills Development in Higher Education? A Systematic Literature Review. European Journal of Education, 60(1), e70036. https://doi.org/10.1111/ejed.70036
Kit Ng, D. T., Luo, W., Chan, H. M. Y. y Chu, S. K. W. (2022). Using digital story writing as a pedagogy to develop AI literacy among primary students. Computers and Education: Artificial Intelligence, 3, 100054. https://doi.org/10.1016/j.caeai.2022.100054
Kong, S. C., Yang, Y. y Hou, C. (2024). Examining teachers’ behavioural intention of using generative artificial intelligence tools for teaching and learning based on the extended technology acceptance model. Computers and Education: Artificial Intelligence, 7, 100328. https://doi.org/10.1016/j.caeai.2024.100328
Law, L. (2024). Application of generative artificial intelligence (GenAI) in language teaching and learning: A scoping literature review. Computers and Education Open, 6, 100174. https://doi.org/10.1016/j.caeo.2024.100174
Lee, S., Choe, H., Zou, D. y Jeon, J. (2026). Generative AI (GenAI) in the language classroom: A systematic review. Interactive Learning Environments, 34(1), 335-359. https://doi.org/10.1080/10494820.2025.2498537
Lepp, M. y Kaimre, J. (2025). Does generative AI help in learning programming:
Students’ perceptions, reported use and relation to performance. Computers in Human Behavior Reports, 18, 100642. https://doi.org/10.1016/j.chbr.2025.100642
Liang, J., Wang, L., Luo, J., Yan, Y. y Fan, C. (2023). The relationship between student interaction with generative artificial intelligence and learning achievement: Serial mediating roles of self-efficacy and cognitive engagement. Frontiers in Psychology, 14, 1285392. https://doi.org/10.3389/fpsyg.2023.1285392
Liu, B., Zhang, W. y Wang, F. (2026). Can Generative Artificial Intelligence Effectively Enhance Students’ Mathematics Learning Outcomes?—A Meta-Analysis of Empirical Studies from 2023 to 2025. Education Sciences, 16(1), 140. https://doi.org/10.3390/educsci16010140
Liu, J., Sun, D., Sun, J., Wang, J. y Yu, P. L. H. (2025). Designing a generative AI enabled learning environment for mathematics word problem solving in primary schools: Learning performance, attitudes and interaction. Computers and Education: Artificial Intelligence, 9, 100438. https://doi.org/10.1016/j.caeai.2025.100438
Liu, X., Guo, B., He, W. y Hu, X. (2025). Effects of Generative Artificial Intelligence on K-12 and Higher Education Students’ Learning Outcomes: A Meta-Analysis. Journal of Educational Computing Research, 63(5), 1249-1291. https://doi.org/10.1177/07356331251329185
Liu, X. y Zhong, B. (2025). Integrating generative Artificial Intelligence into student learning: A systematic review from a TPACK perspective. Educational Research Review, 49, 100741. https://doi.org/10.1016/j.edurev.2025.100741
Ma, N. y Zhong, Z. (2025). A Meta-Analysis of the Impact of Generative Artificial Intelligence on Learning Outcomes. Journal of Computer Assisted Learning, 41(5), e70117. https://doi.org/10.1111/jcal.70117
Medel, C., Britton, S. y Gates, W. F. (2025). An exploration of the role of generative AI in fostering creativity in architectural learning environments. Computers and Education: Artificial Intelligence, 9, 100501. https://doi.org/10.1016/j.caeai.2025.100501
Ng, D. T. K., Chan, E. K. C. y Lo, C. K. (2025). Opportunities, challenges and school strategies for integrating generative AI in education. Computers and Education: Artificial Intelligence, 8, 100373. https://doi.org/10.1016/j.caeai.2025.100373
Ogunleye, B., Zakariyyah, K. I., Ajao, O., Olayinka, O. y Sharma, H. (2024). A Systematic Review of Generative AI for Teaching and Learning Practice. Education Sciences, 14(6), 636. https://doi.org/10.3390/educsci14060636
Oka, N. P. (2023). Examining the Role of ChatGPT as a Learning tool in Promoting Students’ English Language Learning Autonomy relevant to Kurikulum Merdeka Belajar. EDUKASIA Jurnal Pendidikan dan Pembelajaran, 4(2), 921-934. https://doi.org/10.62775/edukasia.v4i2.373
Oliveira, M., Zednik, C., Bombaerts, G., Sadowski, B. y Conijn, R. (2025). Assessing students’ DRIVE: A framework to evaluate learning through interactions with generative AI. Computers and Education: Artificial Intelligence, 9, 100497. https://doi.org/10.1016/j.caeai.2025.100497
Pallant, J. L., Blijlevens, J., Campbell, A. y Jopp, R. (2026). Mastering knowledge: The impact of generative AI on student learning outcomes. Studies in Higher Education, 51(4), 714-735. https://doi.org/10.1080/03075079.2025.2487570
Pesovski, I., Santos, R., Henriques, R. y Trajkovik, V. (2024). Generative AI for Customizable Learning Experiences. Sustainability, 16(7), 3034. https://doi.org/10.3390/su16073034
Pham, T. D., Karunaratne, N., Exintaris, B., Liu, D., Lay, T., Yuriev, E. y Lim, A. (2025). The impact of generative AI on health professional education: A systematic review in the context of student learning. Medical Education, 59(12), 1280-1289. https://doi.org/10.1111/medu.15746
Pozdniakov, S., Brazil, J., Poquet, O., Krusche, S., Berrezueta, S., Sadiq, S. y Khosravi, H. (2026). From knowledge gaps to learning opportunities: Leveraging student questions and dual use of generative AI to support student learning at scale. Computers and Education: Artificial Intelligence, 10, 100509. https://doi.org/10.1016/j.caeai.2025.100509
Rahiem, M. D. H. (2026). Generative AI in higher education in Indonesia: Patterns of use and learning impact. Social Sciences & Humanities Open, 13, 102672. https://doi.org/10.1016/j.ssaho.2026.102672
Rasool, U., Li, J. y Liu, M. (2025). Perceptions of generative AI in teaching and learning: UTAUT and TPACK model-based study of teachers and students. Acta Psychologica, 261, 105827. https://doi.org/10.1016/j.actpsy.2025.105827
Rizvi, S., Waite, J. y Sentance, S. (2023). Artificial Intelligence teaching and learning in K-12 from 2019 to 2022: A systematic literature review. Computers and Education: Artificial Intelligence, 4, 100145. https://doi.org/10.1016/j.caeai.2023.100145
Salinas, D. E., Vilalta, E., Michel, R. y Montesinos, L. (2024). Using Generative Artificial Intelligence Tools to Explain and Enhance Experiential Learning for Authentic Assessment. Education Sciences, 14(1), 83. https://doi.org/10.3390/educsci14010083
Sanusi, I. T., Oyelere, S. S., Vartiainen, H., Suhonen, J. y Tukiainen, M. (2023). A systematic review of teaching and learning machine learning in K-12 education. Education and Information Technologies, 28(5), 5967-5997. https://doi.org/10.1007/s10639-022-11416-7
Schorr, I., Bardach, L., Bühler, B. y Kasneci, E. (2026). Learning-to-learn in the age of generative AI: A scoping review and conceptual framework. Computers and Education: Artificial Intelligence, 10, 100575. https://doi.org/10.1016/j.caeai.2026.100575
Sengar, S. S., Hasan, A. B., Kumar, S. y Carroll, F. (2025). Generative artificial intelligence: A systematic review and applications. Multimedia Tools and Applications, 84(21), 23661-23700. https://doi.org/10.1007/s11042-024-20016-1
Shahzad, M. F., Xu, S., Liu, H. y Zahid, H. (2025). Generative Artificial Intelligence (ChatGPT-4) and Social Media Impact on Academic Performance and Psychological Well-Being in China’s Higher Education. European Journal of Education, 60(1), e12835. https://doi.org/10.1111/ejed.12835
Waluyo, B. y Kusumastuti, S. (2024). Generative AI in student English learning in Thai higher education: More engagement, better outcomes? Social Sciences & Humanities Open, 10, 101146. https://doi.org/10.1016/j.ssaho.2024.101146
Weng, X., XIA, Q., Gu, M., Rajaram, K. y Chiu, T. K. F. (2024). Assessment and learning outcomes for generative AI in higher education: A scoping review on current research status and trends. Australasian Journal of Educational Technology, 40(6), 37-55. https://doi.org/10.14742/ajet.9540
Yakubu, M. N., David, N. y Abubakar, N. H. (2025). Students’ behavioural intention to use content generative AI for learning and research: A UTAUT theoretical perspective. Education and Information Technologies, 30(13), 17969-17994. https://doi.org/10.1007/s10639-025-13441-8
Yan, L., Greiff, S., Teuber, Z. y Gašević, D. (2024). Promises and challenges of generative artificial intelligence for human learning. Nature Human Behaviour, 8(10), 1839-1850. https://doi.org/10.1038/s41562-024-02004-5
Yan, W., Nakajima, T. y Sawada, R. (2024). Benefits and Challenges of Collaboration between Students and Conversational Generative Artificial Intelligence in Programming Learning: An Empirical Case Study. Education Sciences, 14(4). https://doi.org/10.3390/educsci14040433
Ye, X., Zhang, W., Zhou, Y., Li, X. y Zhou, Q. (2025). Improving students’ programming performance: An integrated mind mapping and generative AI chatbot learning approach. Humanities and Social Sciences Communications, 12(1), 558. https://doi.org/10.1057/s41599-025-04846-4
Yusuf, A., Pervin, N., Román, M. y Noor, N. M. (2024). Generative AI in education and research: A systematic mapping review. Review of Education, 12(2), e3489. https://doi.org/10.1002/rev3.3489
Zhou, A. y Luo, Y. (2025). Exploring the impact of generative AI on student learning in accounting. Journal of Accounting Education, 72, 100982. https://doi.org/10.1016/j.jaccedu.2025.100982
Zhou, X., Teng, D. y Al-Samarraie, H. (2024). The Mediating Role of Generative AI Self-Regulation on Students’ Critical Thinking and Problem-Solving. Education Sciences, 14(12), 1302. https://doi.org/10.3390/educsci14121302
Zhu, Y., Liu, Q. y Zhao, L. (2025). Exploring the impact of generative artificial intelligence on students’ learning outcomes: A meta-analysis. Education and Information Technologies, 30(11), 16211-16239. https://doi.org/10.1007/s10639-025-13420-z
Zhuang, Y., Zhao, R., Xie, Z. y Yu, P. L. H. (2025). Enhancing language learning through generative AI feedback on picture-cued writing tasks. Computers and Education: Artificial Intelligence, 9, 100450. https://doi.org/10.1016/j.caeai.2025.100450