A predictive model to explain student persistence in blended and online courses in higher education

Abstract

This study sought to identify the significant predictors of students' persistence in blended and online courses in higher education. Drawing from Choi's model (2016), a structural model, comprising eight predictive and three moderating variables, was tested. The sample was composed of 348 students enrolled at two French-speaking Canadian universities who completed an online questionnaire. Data were analyzed using partial least squares structural equation modelling (PLS-SEM) and partial least squares multigroup analysis (PLS-MGA). The findings suggest that learner autonomy, student satisfaction, perception of a Community of Inquiry, and family responsibilities are the primary factors influencing student persistence in blended and online courses. Furthermore, the model explains between 9.3% and 46.4% of the variance in persistence, depending on whether we examine the moderating effect of age, gender or course modality. The paper presents recommendations for institutions and faculty seeking to enhance student persistence in blended or online courses.