Artificial intelligence as a tool for learning personalization. Potential, challenges, and educational perspectives
Abstract
The review aims to analyze how artificial intelligence (AI) contributes to the personalization of learning by identifying its potentialities, challenges and educational perspectives between 2019 and 2025. A qualitative study was developed under the PRISMA 2020 guidelines reviewing 65 international studies. Three axes were identified: the pedagogical and technological benefits of AI in the adaptation of content and learning rhythms; the ethical, methodological and equity limitations in its implementation; and emerging trends towards smart and inclusive learning ecosystems. The results show that AI allows for more adaptive, autonomous and efficient learning, but its effectiveness depends on teacher mediation, digital literacy and the establishment of ethical frameworks. It is concluded that AI does not replace the teacher but rather expands their ability to personalize and accompany the educational process, if applied responsibly and oriented to the common good.
Downloads
References
Alrakhawi, H. A., Jamiat, N., & Abu-Naser, S. S. (2023). Intelligent tutoring systems in education: a systematic review of usage, tools, effects and evaluation. Journal of Theoretical and Applied Information Technology, 101(4), 1205-1226. https://www.jatit.org/volumes/Vol101No4/6Vol101No4.pdf
Boateng, O., & Boateng, B. (2025). Algorithmic bias in educational systems: Examining the impact of AI-driven decision making in modern education. World Journal of Advanced Research and Reviews, 25(1), 2012-2017. https://doi.org/10.30574/wjarr.2025.25.1.0253
Braun, V., & Clarke, V. (2022). Thematic analysis: A practical guide. SAGE Publications. https://n9.cl/yhk7jf
Chugh, R., Turnbull, D., Morshed, A., Sabrina, F., Azad, S., Md Mamunur, R., ... & Subramani, S. (2025). The promise and pitfalls: A literature review of generative artificial intelligence as a learning assistant in ICT education. Computer Applications in Engineering Education, 33(2), e70002. https://doi.org/10.1002/cae.70002
Essa, S. G., Celik, T., & Human-Hendricks, N. E. (2023). Personalized adaptive learning technologies based on machine learning techniques to identify learning styles: A systematic literature review. IEEE Access, 11, 48392-48409. https://doi.org/10.1109/ACCESS.2023.3276439
Ferguson, R. (2012). Learning analytics: Drivers, developments and challenges. International Journal of Technology Enhanced Learning, 4(5/6), 304–317. https://doi.org/10.1504/IJTEL.2012.051816
Ghimire, A., & Edwards, J. (2024, July). From guidelines to governance: A study of ai policies in education. In International Conference on Artificial Intelligence in Education (pp. 299-307). Cham: Springer Nature Switzerland. https://doi.org/10.1186/s41239-023-00408-3
Giannini, S. (2024). UNESCO perspectives on AI in education: Equity, inclusion and governance. UNESCO. https://n9.cl/qkj4a
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign. https://discovery.ucl.ac.uk/id/eprint/10139722/
Hu, S. (2024). The effect of artificial intelligence-assisted personalized learning on student learning outcomes: A meta-analysis based on 31 empirical research papers. Science Insights Education Frontiers, 24(1), 3873-3894. https://doi.org/10.15354/sief.24.re395
Klioukina, S. V., & Engel, A. (2024). Prácticas de personalización del aprendizaje mediadas por las tecnologías digitales: una revisión sistemática. Edutec, Revista Electrónica De Tecnología Educativa, (87), 236-250. https://doi.org/10.21556/edutec.2024.87.3019
Kohnke, L., Zou, D., Ou, A. W., & Gu, M. M. (2025). Preparing future educators for AI-enhanced classrooms: Insights into AI literacy and integration. Computers and Education: Artificial Intelligence, 8, 100398. https://doi.org/10.1016/j.caeai.2025.100398
Li, S., Zeng, C., Liu, H., Jia, J., Liang, M., Cha, Y., ... & Wu, X. (2025). A meta-analysis of AI-enabled personalized STEM education in schools. International Journal of STEM Education, 12(1), 58. https://doi.org/10.1186/s40594-025-00566-y
Luckin, R., George, K., & Cukurova, M. (2022). AI for school teachers. Routledge. https://n9.cl/stqvi
Merino-Campos, C. (2025). The impact of artificial intelligence on personalized learning in higher education: A systematic review. Trends in Higher Education, 4(2), 17. https://doi.org/10.3390/higheredu4020017
Microsoft Education. (2025). AI in education: A Microsoft special report. Microsoft. https://n9.cl/4gn9a
Naseer, A., Ahmad, N. R., & Chishti, M. A. (2025). Psychological Impacts of AI Dependence: Assessing the Cognitive and Emotional Costs of Intelligent Systems in Daily Life. Review of Applied Management and Social Sciences, 8(1), 291-307. https://doi.org/10.47067/ramss.v8i1.458
Organization for Economic Cooperation and Development [OECD]. (2024). Policies for the digital transformation of school education. https://acortar.link/imLPia
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., Higgins, J. P. T., McGuinness, L. A., Stewart, L. A., Thomas, J., & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372:n71. https://doi.org/10.1136/bmj.n71
Pornpongtechavanich, P., & Wannapiroon, P. (2021). Intelligent interactive learning platform for seamless learning ecosystem to enhance digital citizenship’s lifelong learning. International Journal of Emerging Technologies in Learning (IJET), 16(14), 232-248. https://doi.org/10.3991/ijet.v16i14.22675
Ruiz Miranda, E. (2023). La revolución de la inteligencia artificial en la educación: una reseña de ChatGPT: https://chat.openai.com/. Revista de Estudios e Investigación en Psicología y Educación, 10(1), 156-160. https://doi.org/10.17979/reipe.2023.10.1.9594
Shireesha, M., & Jeevan, J. (2024). The Role of Artificial Intelligence in Personalized Learning: A Pathway to Inclusive Education. Library of Progress-Library Science, Information Technology & Computer, 44(3). https://n9.cl/8ro79
Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–339. https://doi.org/10.1016/j.jbusres.2019.07.039
Tabrizi, H. H., & Jafarie, M. (2023). Intelligent (Language) Tutoring Systems: A Second-order Meta-analytic Review. Journal of Applied Linguistics Studies, 2(1), 30-42. https://oiccpress.com/jals/article/view/5575
UNESCO. (2023). Guidance for generative AI in education and research. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000386693
Zawacki‑Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education — where are the educators? International Journal of Educational Technology in Higher Education, 16, Article 39. https://doi.org/10.1186/s41239-019-0171-0
Copyright (c) 2025 Marjorie Juana Vera-Arias, Rubén Darío Ruiz-Andaluz
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
LICENCIA DE CONTENIDO
Creative Commons
Atribución-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0)
Política propuesta para revistas que ofrecen acceso abierto
Aquellos autores/as que tengan publicaciones con esta revista, aceptan los términos siguientes:
Usted es libre de:
Compartir — copiar y redistribuir el material en cualquier medio o formato
Adaptar — remezclar, transformar y construir a partir del material
La licenciante no puede revocar estas libertades en tanto usted siga los términos de la licencia
Bajo los siguientes términos:
Atribución — Usted debe dar crédito de manera adecuada, brindar un enlace a la licencia, e indicar si se han realizado cambios. Puede hacerlo en cualquier forma razonable, pero no de forma tal que sugiera que usted o su uso tienen el apoyo de la licenciante.
NoComercial — Usted no puede hacer uso del material con propósitos comerciales.
CompartirIgual — Si remezcla, transforma o crea a partir del material, debe distribuir su contribución bajo la lamisma licencia del original.
No hay restricciones adicionales — No puede aplicar términos legales ni medidas tecnológicas que restrinjan legalmente a otras a hacer cualquier uso permitido por la licencia.
DERECHOS DE AUTOR Y PERMISO
La revista permite que los autores tengan los derechos de autor sin restricciones.
La revista permite que los autores conserven los derechos de publicación sin restricciones; y garantizan a la revista el derecho de ser la primera publicación del trabajo.
