Year: 2025
Type: article
Abstract: This study aims to develop a predictive model for student completion rates in the Faculty of Science at the University of Tabuk, focusing on academic factors including withdrawal rate, suspension rate, deregistration rate, weighted percentage, first-year failure rate, and academic guidance rate. A copula-based approach is employed to analyze the complex interdependencies among these factors and their varying effects on male and female students. The findings indicate that female students exhibit higher completion rates and stronger academic correlations, as captured by the Gumbel copula, which highlights significant upper-tail dependence. In contrast, male students show weak or no dependence between academic factors, suggesting more independent academic behaviors. Classical regression analysis revealed that most of the parameters were not statistically significant as well as issues of multicollinearity, reinforcing the necessity of copula-based models to accurately capture these relationships. The study underscores the importance of targeted interventions, particularly for male students, to improve completion rates. These results help create strategies based on data to improve student success and make the institution more effective.
Author: ELsiddig Idriss Mohamed
Language: English
Subfield: Demography
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4410132209