Predictive capacity of a PLS-SEM model on intention to drop out of university during COVID-19

Abstract

One of the sectors where the COVID-19 pandemic has had the greatest impact has been education. In a hasty way and with little time to react, an interruption of academic normality had to be carried out and a virtual teaching modality had to be transitioned. Not only the teachers, who have had to adapt and modify the teaching-learning processes, but also the students have been affected by this drastic change of direction that has occurred in higher education. In a key phase of the course, with social and family conditions not always favorable, with lack of resources and with the distance imposed by alarm measures, students have been subjected to pressure that has put the continuity of studies. METHOD: The study carried out with a sample of 475 students from different undergraduate degrees from the University of La Laguna (Spain), aimed to validate a predictive model on the intention to abandon, using a structural equation model. Specifically, the predictive value that the virtual teaching model, academic exhaustion and expectations of self-efficacy had in the intention of dropping out of university students was analyzed. RESULTS: The results showed that the resulting model was valid to predict the variable of intention to abandon the studies. DISCUSSION: The data obtained can help prevent situations of risk of abandonment in the future, through the implementation of guidance, information, academic support and student monitoring programs.