Enseñanza personalizada con sistemas de recomendación educativos, redes de ontologías y docente-in-the-loop
DOI:
https://doi.org/10.24215/18509959.43.e1Palabras clave:
Sistemas de recomendación educativos, Enseñanza personalizada, Docente-in-the-Loop, Redes basadas en OntologíasResumen
Este artículo examina el papel de las Tecnologías de la Información y la Comunicación (TIC) en la educación, centrándose en desafíos como la brecha digital y el auge de la inteligencia artificial generativa. Si bien estas tecnologías amplían las oportunidades de aprendizaje, también profundizan desigualdades, lo que resalta la necesidad de estrategias inclusivas. La enseñanza personalizada, respaldada por Sistemas de Recomendación Educativos (SRE), adapta la instrucción a las necesidades del estudiantado; sin embargo, muchos SRE priorizan la eficiencia algorítmica sobre la pedagogía. El enfoque Docente-in-the-Loop (DITL) aborda esta limitación al integrar la experiencia de los educadores, garantizando recomendaciones contextualmente pertinentes. Este estudio propone un Marco de Enseñanza Personalizada que combina redes basadas en ontologías con SRE y DITL para mejorar la adaptabilidad y la inclusión. A través de un estudio de caso y una revisión de la literatura, se explora cómo la intervención docente en los SRE puede responder mejor a la diversidad estudiantil. Al avanzar en el desarrollo de sistemas de recomendación éticos y pedagógicamente sólidos, esta investigación contribuye al debate global sobre una educación equitativa y de alta calidad que equilibre el avance tecnológico con la enseñanza centrada en las personas.
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[1] M. Viola, D. de Queiroz, and R. Motz, "Is the Human-in-the-Loop Concept Applied in Educational Recommender Systems?," in Perspectives and Trends in Education and Technology, A. Mesquita, A. Abreu, J. V. Carvalho, C. Santana, and C. H. P. de Mello, Eds. Singapore: Springer, 2023, pp. 61–67, doi: 10.1007/978-981-99-5414-8_61.
[2] M. Morán and A. Watters, "The Problem with Personalization," EdSurge, 2017. [Online]. Available: https://www.edsurge.com. [Accessed: May 2025].
[3] T. R. Gruber, "A Translation Approach to Portable Ontology Specifications," Knowl. Acquis., vol. 5, no. 2, pp. 199–220, 1993.
[4] J. F. Calderero Hernández, A. M. Aguirre Ocaña, A. Castellanos Sánchez, R. M. Peris Sirvent, and P. Perochena González, "Una nueva aproximación al concepto de educación personalizada y su relación con las TIC," Teoría de la Educación. Educación y Cultura en la Sociedad de la Información, vol. 15, no. 2, pp. 131–151, 2014.
[5] M. L. Bernacki, M. J. Greene, and N. G. Lobczowski, "A Systematic Review of Research on Personalized Learning: Personalized by Whom, to What, How, and for What Purpose(s)?," Educational Psychology Review, vol. 33, pp. 1675–1715, 2021, doi: 10.1007/s10648-021-09615-8.
[6] N. S. Raj and V. G. Renumol, "An Improved Adaptive Learning Path Recommendation Model Driven by Real-Time Learning Analytics," Journal of Computers in Education, pp. 1–28, Dec. 2022, doi: 10.1007/s40692-022-00250-y.
[7] F. O. Isinkaye, Y. O. Folajimi, and B. A. Ojokoh, "Recommendation Systems: Principles, Methods, and Evaluation," Egyptian Informatics Journal, vol. 16, no. 3, pp. 261–273, 2015, doi: 10.1016/j.eij.2015.06.005.
[8] V. Maphosa and M. Maphosa, "Fifteen Years of Recommender Systems Research in Higher Education: Current Trends and Future Direction," Applied Artificial Intelligence, vol. 37, no. 1, pp. 406–442, 2023.
[9] S. Sergis, P. Zervas, and D. G. Sampson, "Towards Learning Object Recommendations Based on Teachers’ ICT Competence Profiles," in Proceedings of the 14th International Conference on Advanced Learning Technologies (ICALT), IEEE, 2014, pp. 534–538.
[10] J. Buder and C. Schwind, "Learning with Personalized Recommender Systems: A Psychological View," Computers in Human Behavior, vol. 28, no. 1, pp. 207–216, 2012, doi: 10.1016/j.chb.2011.10.016.
[11] S. Garcia-Martinez, "Educational Recommender Systems: A Pedagogical-Focused Perspective," in Multimedia Services in Intelligent Environments, 2013, pp. 113–124, doi: 10.1007/978-3-319-00375-7_8.
[12] J. J. Gonçalves da Silva, M. L. de Oliveira, and W. da Silva, "Educational Technologies and Personalization of Education: Challenges and Opportunities," RCMOS – Multidisciplinary Scientific Journal O Saber, vol. 4, no. 1, pp. 1–10, 2024.
[13] N. Arambepola and L. Munasinghe, "Human in the Loop Design for Intelligent Interactive Systems: A Systematic Review," in Proceedings of the International Conference on Applied and Pure Sciences, vol. 1, 2021, pp. 64–70.
[14] C. Feilmayr and W. Wöß, "An Analysis of Ontologies and Their Success Factors for Application to Business," Data & Knowledge Engineering, vol. 115, pp. 91–112, 2018, doi: 10.1016/j.datak.2018.01.001.
[15] M. Deschênes, "Sistemas de recomendación para apoyar la autonomía de los estudiantes en un contexto de aprendizaje: una revisión sistemática," International Journal of Educational Technology in Higher Education, vol. 17, p. 50, 2020, doi: 10.1186/s41239-020-00219-w.
[16] J. K. Tarus, Z. Niu, and G. Mustafa, "Knowledge-Based Recommendation: A Review of Ontology-Based Recommender Systems for E-Learning," Artificial Intelligence Review, vol. 50, no. 1, pp. 21–48, 2018, doi: 10.1007/s10462-017-9539-5.
[17] J. Joy and R. V. Govinda Pillai, "Review and Classification of Content Recommenders in E-Learning Environment," Journal of King Saud University – Computer and Information Sciences, vol. 34, no. 9, pp. 7670–7685, 2022, doi: 10.1016/j.jksuci.2021.06.009.
[18] A. Agarwal and M. Chauhan, "Similarity Measures Used in Recommender Systems: A Study," International Journal of Engineering Technology Science and Research, vol. 4, no. 6, pp. 619–626, Jun. 2017.
[19] A. Diaz, R. Motz, E. Rohrer, and L. Tansini, "An Ontology Network for Educational Recommender Systems," in Educational Recommender Systems and Technologies: Practices and Challenges, Hershey, PA, USA: IGI Global, 2011, pp. 67–93, doi: 10.4018/978-1-61350-489-5.ch004.
[20] M. Feldstein, "The Future of Education Is Personalized," EdSurge, 2019. [Online]. Available: https://www.edsurge.com. [Accessed: May 2025].
[21] P. Freire, Pedagogy of the Oppressed. New York, NY, USA: Continuum, 1970.
[22] G. Lampropoulos, "Recommender Systems in Education: A Literature Review and Bibliometric Analysis," Advances in Mobile Learning Educational Research, vol. 3, no. 2, pp. 829–850, 2023, doi: 10.25082/AMLER.2023.02.011.
[23] R. Pathak, F. Spezzano, and M. S. Pera, "Understanding the Contribution of Recommendation Algorithms on Misinformation Recommendation and Misinformation Dissemination on Social Networks," ACM Transactions on the Web, vol. 17, no. 4, Art. 35, pp. 1–26, 2023, doi: 10.1145/3616088.
[24] A. Y. Q. Huang, O. H. T. Lu, and S. J. H. Yang, "Effects of Artificial Intelligence–Enabled Personalized Recommendations on Learners’ Learning Engagement, Motivation, and Outcomes in a Flipped Classroom," Computers & Education, vol. 194, Art. no. 104684, 2023, doi: 10.1016/j.compedu.2022.104684.
[25] J. Li, A. H. Miller, S. Chopra, M. Ranzato, and J. Weston, "Dialogue Learning with Human-in-the-Loop," in Proceedings of the International Conference on Learning Representations (ICLR), 2016.
[26] N. Yanes, "A Machine Learning-Based Recommender System for Improving Students Learning Experiences," IEEE Access, vol. 8, pp. 201218–201235, 2020, doi: 10.1109/ACCESS.2020.3036336.
[27] A. J. Fernandez Garcia, R. Rodriguez-Echeverria, J. Preciado, J. María, J. M. Conejero Manzano, and F. Sánchez-Figueroa, "Creating a Recommender System to Support Higher Education Students in the Subject Enrollment Decision," IEEE Access, vol. 8, pp. 158440–158448, 2020, doi: 10.1109/ACCESS.2020.3031572.
[28] F. Amato, V. Moscato, A. Picariello, and F. Piccialli, "SOS: A Multimedia Recommender System for Online Social Networks," Future Generation Computer Systems, vol. 93, pp. 914–923, 2019, doi: 10.1016/j.future.2017.04.028.
[29] H. Ko, S. Lee, Y. Park, and A. Choi, "A Survey of Recommendation Systems: Recommendation Models, Techniques, and Application Fields," Electronics, vol. 11, no. 1, Art. no. 141, 2022, doi: 10.3390/electronics11010141
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Derechos de autor 2026 Maria Viola; Daniel de Queiroz, Regina Motz
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