Thinking Shapes Learning: The Predictive Power of Cognitive Abilities in the First Year of Engineering

Resumen

This study examines the predictive relationship between cognitive abilities assessed during the university admission process—specifically mathematical, spatial, and verbal reasoning—and academic performance after the first semester of engineering education. The aim is to identify which cognitive components best forecast students’ early success in STEM-related diagnostic evaluations. A correlational, ex post facto, longitudinal design was applied using institutional data from a higher education institution based in Ecuador. The dataset included 4,813 applicants who completed the Admission Aptitude Test and 248 students who later undertook disciplinary diagnostic tests in Mathematics, Physics, Chemistry, and Language after a leveling semester. Correlation and multiple regression analyses were conducted to examine associations and predictive effects. Mathematical aptitude was the strongest and most consistent predictor of diagnostic performance, particularly in Mathematics and Chemistry. Spatial aptitude showed moderate predictive power in Physics and Chemistry, whereas verbal aptitude exhibited weak or nonsignificant relationships, especially in Language. These results confirm the central role of quantitative reasoning in early engineering achievement. The study is limited to one institution and one admission cycle, restricting generalizability. Future research should explore longitudinal effects and integrate non-cognitive variables such as motivation and self-efficacy to construct more comprehensive predictive models. Findings support incorporating validated aptitude assessments into admission processes and strengthening mathematical and spatial reasoning through preparatory or remedial programs.