Analysis of Factors Associated with Academic Risk Using Logistic Regression in a Higher Education Institution: Contributions to Counseling and Guidance Interventions
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Keywords
higher education, university student, academic performance
Abstract
Objective: To analyze the factors associated with the probability of academic risk among first-year students at a higher education institution.
Method: A quantitative, non-experimental, and correlational study was conducted with 527 first-year students. Logistic regression was used to analyze academic, sociodemographic, and psychoeducational variables. Model fit and discriminative capacity were evaluated using goodness-of-fit indicators, a ROC curve, and 10-fold cross-validation.
Results: Five factors showed statistically significant associations with academic risk. Being male was associated with higher odds of risk (OR = 2.43; 95% CI: 1.61–3.71), while holding a scholarship was related to lower odds (OR = 0.60; 95% CI: 0.38–0.94). Furthermore, for every 0.1-unit increase, the digital index showed a protective association (OR = 0.84; 95% CI: 0.75–0.95), whereas the technological index showed a positive association (OR = 1.17; 95% CI: 1.02–1.34). Every 10-point increase in the admission score was associated with lower odds of risk (OR = 0.97; 95% CI: 0.94–0.99). The model achieved an AUC of 0.704.
Conclusions: This study contributes to the field of educational counseling and guidance by providing an empirical framework for the early detection of conditions that compromise student retention, academic achievement, and educational trajectories. Additionally, it generates actionable data to support subsequent assessment and intervention processes tailored to individual needs and contextual conditions.
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