Text mining in the analysis of experiences of higher-education students in the migration to the online study model forced by Covid-19

Abstract

This paper analyzes the experiences of higher education students in the migration from face-to-face education to online education in the context of COVID-19. To carry out the analysis, we collected experiences of students of the Computer Engineering program of the Universidad del Istmo, Tehuantepec Campus, Oaxaca (Mexico), in the months of March-July 2021. The analysis was conducted using text mining tools, starting with an exploration of the data through word clouds, bi-grams to penta-grams, co-occurrence networks, and control items. The results of the analysis indicated that the teacher maintained a central role, that the pedagogical content that the students experienced was based on unstructured environments with a tendency to trial and error, that it is necessary to know the cognitive and affective profile of students in order to define an adequate pedagogical content in the study plans and programs, and even to take into account technologies such as artificial intelligence to improve the educational experiences of teachers and students.