Motivated Learning and Self-Regulation as Predictors of Satisfaction and Attrition Intentions in First-Year University Students

Abstract

This study investigated the influence of motivated learning and self-regulation on university students' academic satisfaction and attrition intentions. Using a quantitative, cross-sectional, and predictive associational design with a sample of 287 first-year students from engineering, economics, social sciences, and law programs at a private Venezuelan university. Data was collected using the Conscious Motivated Learning Scale, the Self-Regulation Processes Inventory, and single-item measures of academic satisfaction and attrition intentions. Data analysis included descriptive and inferential statistics, as well as logistic regressions. The results revealed positive and significant correlations between academic satisfaction and self-regulated learning, as well as with motivated learning dimensions (affective goals, social goals, personal motives, and attribution to achievement). Conversely, attrition intentions showed negative and significant correlations with these variables. Significant differences were also found based on the attrition intention and academic satisfaction level. We concluded that personal motives, affective goals, and self-regulated learning significantly predict academic satisfaction. Task goals and certain study conditions appeared to decrease satisfaction. University satisfaction emerged as the strongest predictor of reduced attrition intentions, followed by significant inverse associations with affective goals and student engagement, alongside self-regulated learning. These findings suggest the importance of strategies that foster intrinsic motivation and self-regulation to promote retention and academic well-being.