Modelling Student Dropout Risk Using Survival Analysis and Analytic Hierarchy Process for an Undergraduate Accounting Program

Abstract

A combination of mathematical and statistical modelling techniques may be used to analyse student dropout behaviour. The aim of this study is to combine Survival Analysis and Analytic Hierarchy Process methodologies when identifying students at-risk of dropping out. This combination favours the institutional understanding of dropout as a dynamic phenomenon, susceptible to preventative measures and increased efficiency, leading to the curbing of dropout rates. These techniques quantify and qualify the student risk of dropout from an academic program and estimate the probability of persistance, considering the variables framed in academic, institutional, socioeconomic, and individual factors. These factors are provided by the habitus immersed in the particular institutional educational project. The proposal was tested with real data, evaluating the operability and viability of both Survival Analysis and Analytic Hierarchy Process methods. Type of admission, gender, and age were found to be the most influential variables of survival. This novel combination of methods could offer possibilities for decision-making of use in the strengthening of institutional information culture and student support programs, and in efficient allocation of resources.