Detecting at-risk students on Computer Science bachelor programs based on pre-enrollment characteristics

Erika B Varga,Ádám Sátán

doi:10.1556/063.2021.00017

Abstract

AbstractThe purpose of this paper is to investigate the pre-enrollment attributes of first-year students at Computer Science BSc programs of the University of Miskolc, Hungary in order to find those that mostly contribute to failure on the Programming Basics first-semester course and, consequently to dropout. Our aim is to detect at-risk students early, so that we can offer appropriate mentorship program to them. The study is based on secondary school performance and first-semester Programming Basics course results from the last decade of over 500 students. Secondary school performance is characterized by the rank of the school, admission point score, and foreign language knowledge. The correlation of these data with the Programming Basics course result is measured. We have tested three hypotheses, and found that admission point score and school rank together have significant impact on the first-semester Programming Basics course results. The findings also support our assumption that students having weaknesses in all examined pre-enrollment attributes are subject to dropout. This paper presents our analysis on students' data and the method we used to determine the attributes that mostly affect dropout.

Highlights

In the Europe 2020 strategy, one of the goals is to have at least 40% of 30–34-year-olds complete higher education (Vossensteyn et al, 2015)
The purpose of this paper is to investigate the pre-enrollment attributes of first-year students at Computer Science BSc programs of the University of Miskolc, Hungary in order to find those that mostly contribute to failure on the Programming Basics first-semester course and, to dropout
In order to decrease dropout rates, universities need to take interventional steps to assure that the students remain in the system and achieve the learning outcomes required for completing a degree

Summary

Introduction

In the Europe 2020 strategy, one of the goals is to have at least 40% of 30–34-year-olds complete higher education (Vossensteyn et al, 2015). This is in accordance with the global trends, since there is a world-wide observation that economy is best served by maximizing the level of education in the population (Yorke, 2004). For this reason national governments tend to widen participation in tertiary education. In order to decrease dropout rates, universities need to take interventional steps to assure that the students remain in the system and achieve the learning outcomes required for completing a degree

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Conclusion