Analysis of learning styles in engineering students after the COVID-19 pandemic

Abstract

The research was carried out with the objective of knowing aspects that are interesting for researchers about learning; such as the analysis of the learning styles currently in the post-pandemic period, manifested by students of different degrees. Identifying and analyzing learning styles and relating them to current teaching practices will allow applying teaching strategies that could reduce the current high dropout and failure rates. The results obtained show the trends by educational institution, by semester and by career. Significant differences were found in the results in the active style between schools; by semester, most of the students of the initial semesters are visual and sensitive, in later semesters, there is a tendency to be intuitive and by career they show a tendency to be sensitive and visual; As a conclusion, a student can have different learning styles, but in general they have a certain affinity for a learning profile. Objective. Identify and analyze the current learning styles in Engineering students, derived from the abrupt changes in study modalities that occurred due to the Covid 19 pandemic. Methodology. A validated survey (Cronbach's : 0.872) was applied to students of Electrical Engineering, Electronic Engineering and Biochemical Engineering. The following learning styles were considered to be identified and analyzed: active-reflexive, sensitive-intuitive, visual-verbal, and sequential-global. A scale of dichotomous variables was chosen, they were valued according to the proposal of Felder and Silverman (Felder and Silverman, 1988), the answers were set in the categories of learning styles proposed by the author in active or reflective, sensitive or revealing, visual or verbal, and sequential or global, were quantified, tabulated, and analysis of variance (ANOVA) for parametric samples. Contribution. This research made it possible to identify the learning styles of undergraduate students in the post-pandemic period, to find out the current learning preferences, which can be applied to propose, where appropriate, the necessary adjustments within the teaching strategies of teachers interested in reduce the current high rate of failure and dropout.