Abstract:

Technological advances such as Massive Open Online Courses (MOOCs) and Information and Communication Technologies (ICT) allow the construction of new spaces where students consult the information at any time, take the online exams and communicate with the participants of the educational process from anywhere. This quantitative research analyzes the perception of the teachers about the organization of the school activities in MOOCs and use of ICT considering machine learning and decision tree techniques (data science). The participants are 122 teachers (58 men and 64 women) from the National Autonomous University of Mexico who took the “Innovation in University Teaching 2020” Diploma. The academic degree of these educators is Bachelor (n = 35, 28.69%), Specialty (n = 4, 3.28%), Master (n = 58, 47.54%) and Doctorate (n = 25, 20.49%). The results of machine learning (linear regressions) indicate that the organization of the school activities in MOOCs positively influences the motivation, participation and learning of the students. Data science identifies 3 predictive models about MOOCs and ICT through the decision tree technique. According to the teachers of the National Autonomous University of Mexico, the organization of the school activities in MOOCs and use of ICT play a fundamental role during the COVID-19 pandemic. The implications of this research promotes that educators use MOOCs and ICT to improve the educational conditions, create new remote school activities and build new virtual learning spaces. In conclusion, universities with the support of technological tools can improve the teaching-learning process and update the course during the COVID-19 pandemic. In particular, MOOCs represent a technological alternative to transform the school activities in the 21st century.

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