Assessment of student pass rate based on correlation and regression models

Abstract

This paper presents a case study exploring the use of correlation and regression models to evaluate and predict the promotion rate of students at the Technical University of Moldova, a public higher education institution in the Republic of Moldova. Static correlation models are used to examine the relationships between academic performance and results achieved throughout the years of study. While linear and logistic regression models are applied to estimate the prediciton of student promotion and successful graduation. The paper highlights the importance of these tools in identifying relevant factors influencing academic success and in developing effective educational strategies to improve promotion rates and reduce the risk of university dropout.