Successful factors in statistics learning for non-STEM courses students: a PLS-PM approach

Abstract

The paper focuses on factors affecting students’ performance in undergraduate statistics courses. Specifically, this study examines the effect of students’ math knowledge, amotivation, self-efficacy, test anxiety, attitude toward statistics and statistical anxiety on performance in higher education. Data was collected from 201 Italian psychology students enrolled in an undergraduate introductory statistics course. The partial least squares path modeling (PLS-PM) was used to test our hypothesis. Overall, our findings show the potential role of math knowledge, test anxiety and attitude toward statistics as predictors of statistics performance. Instead, statistical anxiety is not significantly related to students’ performance. Finally, directions for future research and practical implications of the findings are also discussed.