A path model of university dropout predictors: the role of satisfaction, the use of self-regulation learning strategies and students' engagement

• Autor(a) principal: Bernardo, Ana B.
• Data de Publicação: 2022
• Outros Autores: Galve-González, Celia, Núñez, José Carlos, Almeida, Leandro S.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: https://hdl.handle.net/1822/78462
• topic: Higher education; Dropout; Satisfaction; Learning strategy; Regression analysis; Science & Technology

University dropout is a phenomenon that is a concern in many countries all over the world. However, although there are studies in which the direct relationship of the personal and contextual variables is observed individually to predict dropout, there is little research to know whether any of these variables mediate each other in a more dynamic and complex model. Thus, the objective of this study was to analyze the extent to which the intention to drop out of university courses is predicted by (i) satisfaction and expectations with the course, (ii) engagement with the course, and (iii) by the use of Self-Regulated Learning (SRL) strategies. Eight hundred and seventy-seven students from two Spanish universities completed the CARE questionnaire. Path analyses were performed using Mplus 8.3. The data obtained indicate that the intention to drop out is directly and significantly explained by students´ engagement (in 17.8%) and indirectly explained by the use of SRL strategies through engagement. Changes in engagement and in the use of SRL strategies were seen to be associated with satisfaction. Finally, the effect of satisfaction and the use of SRL strategies explained a proportion of students’ engagement (53.6%). It is important for research or interventions focused on students’ intention to drop out to understand that there are multiple variables that both directly and indirectly influence those intentions.