Abstract
The learning style is characterized by the preferences that the student is acquiring throughout his life and with the interaction in the environment in which he develops. As a traditional method to identify the learning style, the application of questionnaires is carried out; however, they may present inaccurate results due to lack of interest in answering the questionnaires. Currently, there are automatic methods to identify the learning style as the observation of the student’s behavior, while interacting with learning objects in an academic course. Learning objects are those digital tools such as chat rooms, reading materials, exams, among others. These objects allow the actions carried out to be recorded and stored in order to be studied. Therefore, this study presents an evolutionary algorithm to optimize the grouping of students according to their learning style based on the structured learning objects. Thus, the objective is to form groups according to the value of the actions carried out in an academic course and to predict the learning style.
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References
Abdoun, O., Tajani, C., Abouchabaka, J.: Analyzing the performance of mutation operators to solve the traveling salesman problem. Int. J. Emerg. Sci 2(1), 61–77 (2012)
Bernheim, C.T.: El constructivismo y el aprendizaje de los estudiantes. Universidades 48, 21–32 (2011)
Castro, S., de Castro, B.G.: Los estilos de aprendizaje en la enseñanza y el aprendizaje: Una propuesta para su implementacón. Revistas de investigación 29(58) (2017)
Castro, S., Rivas de Rojas, N.: Bailemos al son que nos toquen: una simulación instruccional para mediar sobre el aprendizaje de los estados de agregación de la materia. Investigación y postgrado 23(2), 271–293 (2008)
Egaña, M., Diago, L., Revuelta, M.J., González, P.: Análisis de herramientas de medición de los estilos de aprendizaje 1 analysis of the learning styles measurement tools. Revista de educación 381, 95–131 (Julio-Septiembre 2018). https://doi.org/10.4438/1988-592X-RE-2017-381-382
Espinoza-Poves, J.L., Miranda-Vílchez, W.A., Chafloque-Céspedes, R.: Los estilos de aprendizaje vark en estudiantes universitarios de las escuelas de negocios. Propósitos y representaciones 7(2), 384–414 (2019)
Farías, R., Durán, E.B., Figueroa, S.G.: Las técnicas de clustering en la personalización de sistemas de e-learning. In: XIV Congreso Argentino de Ciencias de la Computación (2008)
Felder, R.M.: Learning and teaching styles in engineering education (2002)
Felder, R.M., Spurlin, J.: Applications, reliability and validity of the index of learning styles. Int. J. Eng. Educ. 21(1), 103–112 (2005)
Franco, M.E.E., García, M.F.V., Estrada, R.M.F., Estrada, M.d.R.F., Medina, M.d.l.L.S.: Estilos de aprendizaje en la facultad de odontología. Revista RedCA 1(2), 86–100 (2018)
Gibson, E.J.: Perceptual learning and the theory of word perception. Cogn. Psychol. 2(4), 351–368 (1971)
González, B., León, A.: Procesos cognitivos: De la prescripción curricular a la praxis educativa. Revista de Teoría y Didáctica de las Ciencias Sociales 19, 49–67 (2013)
Jh, H.: Adaptation in natural and artificial systems. Ann Arbor (1975)
Mahesh, B.: Machine learning algorithms-a review. Int. J. Sci. Res. (IJSR).[Internet] 9, 381–386 (2020).
Páez, H., Arreaza, E.: Uso de una plataforma virtual de aprendizaje en educación superior.: Caso nicenet. org of a virtual learning platform in higher education. case study: Nicenet. org. Paradigma (2015)
Parfenov, D., Zaporozhko, V.: Implementation of genetic algorithm for forming of individual educational trajectories for listeners of online courses. In: Instrumentation engineering, electronics and telecommunications-2018, pp. 72–82 (2018)
Sarmiento, Santana, M.: La enseñanza de las matemáticas y las ntic. una estrategia de formación permanente. Universitat Rovira I Virgili 49 (2007)
Soloman, B.A., Felder, R.M.: Index of learning styles questionnaire. NC State University. https://www.engr.ncsu.edu/learningstyles/ilsweb.html (last visited on 14.05. 2010) 70 (2005)
Stash, N.V., Cristea, A.I., De Bra, P.M.: Authoring of learning styles in adaptive hypermedia: problems and solutions. In: Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters, pp. 114–123 (2004)
Yannibelli, V., Godoy, D., Amandi, A.: A genetic algorithm approach to recognise students’ learning styles. Interact. Learn. Environ. 14(1), 55–78 (2006)
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We thank Autonomous University of the State of Mexico and CONACYT.
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Pineda-Arizmendi, M.G., Hernández-Castañeda, Á., García-Hernández, R.A., Ledeneva, Y., Cruz Reyes, J.R. (2023). Automatic Identification of Learning Styles Through Behavioral Patterns. In: Rodríguez-González, A.Y., Pérez-Espinosa, H., Martínez-Trinidad, J.F., Carrasco-Ochoa, J.A., Olvera-López, J.A. (eds) Pattern Recognition. MCPR 2023. Lecture Notes in Computer Science, vol 13902. Springer, Cham. https://doi.org/10.1007/978-3-031-33783-3_8
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