Adaptive learning and data analytics as fundamentals of a computer system to improve the teaching-learning process in Moodle

  • Verónica López Martínez Universidad Autónoma de Querétaro
  • Ma. Teresa García Ramírez Universidad Autónoma de Querétaro
  • Sofía Amadis Rivera López Universidad Autónoma de Querétaro
Keywords: Adaptive learning, data analysis, educational platforms, teaching-learning

Abstract

Now days, the teachers need technological tools that promote the development of the teaching-learning process, regardless of the modality in which they develop and that respond to the demands that students, need to promote their learning effectively. In view of this, the main objective of this work is the proposal of a computer system that, through data analysis and adaptive learning, provides teachers with a simpler way to analyze and adapt their virtual contents, according to the requirements and needs of their students. A descriptive methodology has been followed to identify and characterize the phenomena, situations and events that affect the development of courses in virtual modalities and that, in the same way, led us to present a proposal to arrive at the finding that it is possible to measure and adapt the indicators of the teaching-learning process of students in technological educational platforms, through the analysis of their data.

References

Alonso-Fernández, C., Calvo-Morata, A., Freire, M., Martínez-Ortiz, I. and Fernández-Manjón, B. (2019). Applications of data science to game learning analytics data: A systematic literature review. Computers and Education, 141(April), 103612. https://doi.org/10.1016/j.compedu.2019.103612

Avello, R. y Duart, J. M. (2016). Nuevas tendencias de aprendizaje colaborativo en e-learning. Claves para su implementación efectiva. Estudios Pedagógicos, 42(1), 271–282.

Ayala, R. (2021). Zooming in on virtual education: biopolitics and student-centred learning. Educacion Medica, 22(3), 177–180. https://doi.org/10.1016/j.edumed.2021.01.004

Cáceres-Reche, P., Rodríguez-García, A.-M., Gómez, G. y Rodríguez, C. (2020). Analíticas de aprendizaje en educación superior: una revisión de la literatura científica de impacto. IJERI: International Journal of Educational Research and Innovation, 13, 32–46. https://doi.org/10.46661/ijeri.4584

Cortés Pérez, E., Acuña Gamboa, A. y Martínez Mendoza, E. (2021). La covid-19 y el aprendizaje adaptativo inteligente en la educación superior: una revisión de la literatura. I Congreso Virtual de Educación.

Ferreira, A. C., Altamirano, M., Ortega, M. D. L. Á. L. y González, O. A. G. (2019). Analítica del aprendizaje y las neurociencias educativas: nuevos retos en la integración tecnológica. Revista Iberoamericana de Educación, 80(1), 31-54. https://doi.org/10.35362/rie8013428

Hssina, B. and Erritali, M. (2019). A personalized pedagogical objectives based on a genetic algorithm in an adaptive learning system. Procedia Computer Science, 151, 1152-1157. https://doi.org/10.1016/j.procs.2019.04.164

Iqbal, R., Faiyas, D., More, B., Mahmund, S. and Yousuf, U. (2018). Technological Forecasting & Social Change Big data analytics : Computational intelligence techniques and application areas. Technological Forecasting & Social Change, 153. https://doi.org/10.1016/j.techfore.2018.03.024

Lerís, D., Vea, F. y Velmazán, Á. (2015). Aprendizaje adaptativo en Moodle: tres casos prácticos. Education in the Knowledge Society (EKS), 16(4), 138. https://doi.org/10.14201/eks201516138157

Méndez, S., Romo, A., Cuevas, R. y Sampieri, H. (2016). Manual introductorio al SPSS Statistics Standard Edition 22. https://www.fibao.es/media/uploads/manual_de_spss_universidad_de_celaya.pdf

Monje, C. A. (2011). Metodología de la investigación cuantitativa y cualitativa. Guía didáctica. Universidad Surcolombiana. https://www.uv.mx/rmipe/files/2017/02/Guia-didactica-metodologia-de-la-investigacion.pdf

Navarro, J., Amo, D., Canaleta Llampallas, X., Vidaña-Vila, E. y Martínez, C. (2018). Utilizando analítica del aprendizaje en una clase invertida: experiencia de uso en la asignatura de Sistemas Digitales y Microprocesadores. Universidad de Alicante.

Nessipbayeva, O. and Egger, R. (2015). A Comparative Study of Teaching Style and Infrastructure of Learning of Higher Education in Austria and Kazakhstan. Procedia - Social and Behavioral Sciences, 197(February), 1271–1277. https://doi.org/10.1016/j.sbspro.2015.07.399

Pliakos, K., Joo, S. H., Park, J. Y., Cornillie, F., Vens, C. and van den Noortgate, W. (2019). Integrating machine learning into item response theory for addressing the cold start problem in adaptive learning systems. Computers and Education, 137, 91–103. https://doi.org/10.1016/j.compedu.2019.04.009

Quiroga-Baquero, L. y Padilla, M. (2014). El concepto de modo lingüístico y su aplicación en los procesos de enseñanza-aprendizaje mediante las TIC´S. Journal of Behavior, Health & Social Issues, 6(1), 9. https://doi.org/10.22201/fesi.20070780.2014.6.1.48518

Santos, A. (2019). Propuesta de un modelo de analítica académica para la educación superior. https://repositorio.grial.eu/bitstream/grial/1673/1/Alejandra Santos PI.pdf

Soler, S. F. y Soler, L. (2012). Usos del coeficiente alfa de Cronbach en el análisis de instrumentos escritos. Revista Médica Electrónica, 34(1), 01–06

Thadani, V., Breland, W. and Dewar, J. (2015). Implicit theories about teaching skills predict university faculty members’ interest in professional learning. Learning and Individual Differences, 40, 163–169. https://doi.org/10.1016/j.lindif.2015.03.026

Published
2023-12-18
Section
Artículos Científicos