Dropout Analysis in Davao Oriental State University
DOI:
https://doi.org/10.55927/eajmr.v4i4.116Keywords:
Student Dropout, Academic Performance, Higher Education, Binary Logistic RegressionAbstract
Student dropout remains a critical challenge in higher education, affecting institutional efficiency and student success. This study aims to determine the key predictors of student dropout at Davao Oriental State University (DorSU) through a longitudinal cohort analysis. The research examines undergraduate students who enrolled at the DOrSU Main Campus, San Isidro, Banaybanay, and Cateel campus during the 2019-2020 academic year. Using Binary Logistic Regression within a longitudinal framework, the study evaluates the influence of SUAST scores, Senior High School (SHS) grades, SHS strand, and General Weighted Average (GWA) on student attrition. Findings reveal that GWA is the most significant predictor of dropout (B = 3.023, p < 0.001, Exp(B) = 20.562), indicating that students with lower academic performance face a substantially higher risk of leaving the university. In contrast, entrance exam scores and SHS grades were not statistically significant predictors. These results emphasize the need for academic interventions and support programs to improve student retention and reduce dropout rates.
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