Use of the deep learning and decision tree techniques to analyze the incorporation of technology in the educational field

Authors

DOI:

https://doi.org/10.1344/der.2025.46.26-39

Keywords:

Technology, ICT, Zoom, LMS, COVID-19, data science

Abstract

The aim of this mixed research is to analyze the perception of the students about the use of Zoom and the Learning Management Systems such as Moodle and Google Classroom in the educational field during the COVID-19 pandemic considered data science. In particular, Zoom facilitates the communication, presentation of contents and resolution of doubts. On the other hand, Moodle and Google Classroom allow the delivery of tasks, consultation of information and realization of discussion forums from anywhere. The participants are 128 students of Psychology (n = 70, 54.69%), Social Work (n = 33, 25.78%) and Geophysics (n = 25, 19.53%) who took the Clinical Method, Urban Problems and Electromagnetic Prospecting courses at the National Autonomous University of Mexico during the 2020 school year. The results of the deep learning technique indicate that the use of Zoom and Learning Management Systems (Moodle and Google Classroom) during the COVID-19 pandemic positively influences the assimilation of knowledge and participation of the students. The decision tree technique identifies 4 predictive models about the use of these technological tools. Finally, Zoom, Moodle and Google Classroom allow transforming the teaching-learning process and updating the school activities during the COVID-19 pandemic.

Author Biography

Ricardo-Adán Salas-Rueda, Instituto de Ciencias Aplicadas y Tecnología, Universidad Nacional Autónoma de México

Doctor en Diseño de Nuevas Tecnologías. Investigador de tiempo completo en el Instituto de Ciencias Aplicadas y Tecnología, Universidad Nacional Autónoma de México.

Maestro en Administración e Ingeniero en Sistemas Electrónicos. Investigador nacional SNI nivel 1 (Conacyt) durante el periodo 2019-2021 y Candidato SNI durante el periodo 2016-2018.

Orcid: http://orcid.org/0000-0002-4188-4610

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Published

2025-02-03

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Peer Review Articles