Predicting the use of learning objects: supporting high school education
Predicción del uso de objetos de aprendizaje: apoyo a la educación secundaria
DOI:
https://doi.org/10.56712/latam.v7i4.6409Palabras clave:
learning objects, predictive model, academic performance, student motivationResumen
Education today faces major challenges compared to the situation before 2020, due to changes in the ways of teaching and learning caused by the difficulties of attending classes during the COVID-19 pandemic. Among the main challenges are the lack of didactic resources, limited technological infrastructure, and the geographical location of many schools, particularly those in rural areas. This research analyzes the effectiveness of a predictive model based on the Random Forest algorithm to suggest personalized learning objects for high school students, through the analysis of academic and behavioral variables such as frequency and time of use of digital resources, motivation, and the perceived impact on comprehension. The findings confirm that the predictive methodology not only supports educational personalization but also generated recommendations tailored to each student’s profile, optimizing the use of digital resources and significantly improving comprehension and academic performance. Validation, carried out through a diagnostic pre-test and a final post-test, demonstrated a significant average improvement of 45.24% in the academic performance of the experimental group that utilized the personalized learning objects suggested by the model. This study proposes the integration of machine learning models as an adaptive strategy in educational environments, highlighting the capacity of data analytics to promote equity, reduce learning disparities, and strengthen student-centered pedagogy.
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Aros, A. S. (2025) Predictive Analysis of the Use of Learning Objects for High Schools in the Teziutlán Region [Master's Thesis, Instituto Tecnológico Superior de Teziutlán]
De Medio, C., Limongelli, C., Sciarrone, F., & Temperani, M. (2019). MoodleREC: A recommendation system for creating courses using the Moodle e-learning platform. Computers in Human Behavior. https://doi.org/10.1016/j.chb.2019.106168
Hadayat Ali, H., Muzammal Hussain, M., Fazil, H., Amjad, F., & Nazir, M. (2024). Navigating the future: Trends and innovation in Education. Qualitative Research, 345-366.
Hernández Osorio, J. del C. (2023). La Deserción Escolar en la Educación Media Superior. Ciencia Latina Revista Científica Multidisciplinar, 7(6), 1676–1700. https://doi.org/10.37811/cl_rcm.v7i6.8801
Hotz, N. (December 9, 2024). What is CRISP DM? Retrieved from Data Science PM: https://www.datascience-pm.com/crisp-dm-2/
J. L. García Cué, J. M. Meraz Escobar, & M. A. Jiménez Velázquez, Learning objects as support in the teaching-learning process (p. 87). Mexico: General Directorate of Publications
National Institute of Statistics and Geography. (2025). Interactive tables-Generic. Retrieved from INEGI: https://www.inegi.org.mx/app/tabulados/interactivos/?pxq=Educacion_Educacion_12_987437b7-5398-4067-8b19-a1cd2ec36b7b
National Institute of Statistics and Geography. (2023). National Survey on the Availability and Use of Information Technologies in Households. Retrieved from INEGI: https://www.inegi.org.mx/programas/endutih/2023/
Global Compact. (January 23, 2025). 17 Development Goals to transform the world. Retrieved from Global Compact Network Spain: https://www.pactomundial.org/que-puedes-hacer-tu/ods/
OpenAI. (2024). ChatGPT (Versión GPT-4o) [Modelo de lenguaje grande]. https://chatgpt.com
Orellana-Cordero, M., García-Herrera, D. G., Erazo-Álvarez, J. C., & Narváez-Zurita, C. I. (2020). Objetos virtuales interactivos con Genial.ly: Una experiencia de aprendizaje matemático en bachillerato. CIENCIAMATRIA, 6(3), 309–332. https://doi.org/10.35381/cm.v6i3.403
Palmera Quintero, L. M., Muñoz Morales, L. A., Guerrero Sumalave, D. F., & Holguín Uribe, Y. (2023). Objeto virtual de aprendizaje para la enseñanza: instrumento de apoyo para la inclusión de la informática en niños con discapacidad visual. Mundo Fesc, 13(27), 38–49. https://doi.org/10.61799/2216-0388.135439
Pulido Ocampo, C. A., Martínez Moreno, P., & Vergara Camacho, J. A. (2016). Learning objects as a teaching resource in the Algorithmic educational experience. In J. A. Hernandez Moral, A. Ronquillo Bolaños, A. B. Celis Domínguez, A. Lagunes Domínguez, A. P. Lorandi Medina, & A. D. Otero Escobar, Trends and challenges in educational innovation: an open debate. Mexico: Foundation for International Higher Education.
Rodríguez, N. W. (2023). Objetos virtuales de aprendizaje en el marco de la educación 4.0: una alternativa pedagógica mediada con las TIC para el logro de aprendizajes significativos. Dialéctica, 1(20). https://doi.org/10.56219/dialctica.v1i20.1669
Serna Martínez, R. E., & Alvites Huamaní, C. G. (2021). Plataformas educativas: herramientas digitales de mediación de aprendizajes en educación. HAMUT’AY, 8(3), 66. https://doi.org/10.21503/hamu.v8i3.2347
Tovar Vidal, M., Zepeda Cortés, C., & Castillo Zacatelco, H. (2019). Objetos de Aprendizaje Abiertos basados en ADDIE. Caso de estudio: Colegio de Posgraduados. En J. L. García Cué, R. C. Medina, & M. A. Jiménez Velázquez (Eds.), Los Objetos de Aprendizaje como apoyo en el proceso de enseñanza-aprendizaje (pp. 87-105). Colegio de Posgraduados.
Triola F. Mario. (2004). Estadística (Pearson Educación, Ed.; 9a ed.).
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Derechos de autor 2026 Adriana Pérez López, Raúl Mora Reyes, Naty Rodríguez Ventura, Sara Aros Alberto
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
