Academic engagement and resilience in undergraduate statistics programs with high involuntary enrollment

Abstract Despite the critical role of data expertise in national development, many students enroll in statistics programs involuntarily due to university admission quotas. This study investigated the determinants of academic engagement among Bachelor of Science (BS) Statistics students using a sequential explanatory mixed-methods design ( N = 262). A One-Way Multivariate Analysis of Variance (MANOVA) revealed a highly significant institutional effect of Academic Year Level on the combined experiential dimensions (Pillai’s Trace = 0.15, F(12, 771) = 3.48, p < .001), establishing the presence of a distinct “Senior Year Surge” where fourth-year students exhibit significantly higher engagement and self-efficacy than underclassmen. Furthermore, a 4 × 2 Factorial ANOVA demonstrated that while initial enrollment status (voluntary vs. involuntary) significantly impacts baseline motivation, it does not interact with year level to limit final-year commitment ( p > .05), proving that the “Senior Year Surge” occurs independently of initial program entry conditions. Spearman’s rank correlation matrix further indicated that Career Perception ( $$\:\rho\:$$ = 0.34) and Motivation/Self-Efficacy ( $$\:\rho\:$$ = 0.45) share the strongest bonds with active engagement, while institutional belongingness remains secondary. Qualitative insights from 122 participants highlighted that while students face severe “mathematical pain” and material precarity (e.g., lack of laptops), their persistence is sustained by the high perceived market utility of the degree. These findings culminate in the Statistics Student Success Framework (SSSF), a validated institutional model proving that for students in high-difficulty technical domains, instrumental career outlook serves as a more potent driver of long-term persistence than baseline interest or social integration.