Programa del congreso

Anxiety about mathematics is a significant barrier to academic success in engineering education; however, its internal organization and contextual determinants during the transition to the first year of university are not yet fully understood. The present study examined mathematical anxiety in first-year engineering students using a person-centered approach and multivariate analysis, with the aim of capturing its heterogeneity and cumulative nature. A cross-sectional study was conducted with 293 first-year students, who were assessed using the Abbreviated Math Anxiety Scale (AMAS). Descriptive analyses, latent profile analysis (LPA), multinomial logistic regression, linear regression, and mediation models were applied.

The results showed moderate levels of math anxiety, with significantly higher activation in assessment contexts compared to learning situations. The LPA identified three distinct profiles of math anxiety low, moderate, and high revealing a heterogeneity that is not captured by overall averages. Profile membership was significantly associated with gender, but not with age. Contextual variables such as perception of mathematical performance, avoidance of mathematical activities, and mathematical anxiety since school age were consistently related to higher anxiety profiles. Mediation analysis showed that school anxiety influences university avoidance both directly and indirectly through current mathematical anxiety, which emerged as the main predictor of belonging to latent profiles.

These findings conceptualize math anxiety as a structured and contextual phenomenon, with direct implications for early detection, academic support, and retention in engineering programs