Using discriminant analysis to identify students at risk

Abstract

In designing any educational intervention one ofen needs to determine what factors are related to success and failure in a course, identify students at risk, evaluate the impact of any new program on student pe~ormance. In this paper we will discuss the use of discriminant analysis as a technique for addressing all of these issues.Discriminant analysis is a statistical technique designed to investigate the differences between two or more groups of people with respect to several underlying variables. This technique is more appropriate than commonly used educational measures (correlations, regression weights, etc.) because the variable being predicted is categorical. Moreover, this approach results in a unit of analysis, predicted category membership, that is more useful in evaluating instructional interventions.We have used discriminant analysis to predict student pe~ormance in an introductory electromagnetism course at Georgia Tech. In this course there is a high failure rate (greater than 30% make a grade of D or F ) which results in a great cost to the institute and to students as success in the course is a prerequisite for all engineering majors. A technique that could identify the factors that are predictive of course pelformunce and identify students who are at risk would be of great benefit to the design, implementation, and evaluation of any educational intervention.We will present a case study with over 1600 engineering majors where discriminant analysis was used successfully to determine the predictors of course performance. We looked at over 15 possible predictor variables (SAT, GPA, etc.) and determined which variables would be most useful in identihing students at risk. Using information available from student's records we were able to successfully predict 50% of the students who eventually failed the class.We will also discuss how discriminant analysis can be used as an evaluation technique. We show that this approach provides results that are both more intelpretable and statistically sound than traditional measures.

Pendekatan Analisis Diskriminan Pada Pembelajaran Daring Di Masa Pandemi Covid-19

“…Analisis diskriminan adalah salah satu analisis multivariat yang dapat digunakan untuk memodelkan hubungan antara variabel respon dengan jenis skala data kategorik (nominal atau ordinal dan bersifat kualitatif) dengan satu atau lebih variabel prediktor dengan jenis data kuantitatif [7]. Analisis diskriminan digunakan untuk mengklasifikasikan suatu individu atau observasi ke dalam kelompok yang saling bebas (mutually exclusive) dan menyeluruh berdasarkan variabel prediktor yang digunakan [8]. Analisis diskriminan pada umumnya mirip dengan regresi linier berganda.…”

A Predictive Model for the Determination of Academic Performance in Private Higher Education Institutions

“…Discriminate analysis was done by [14] to predict the success and failure of students in a specific physics course. Discriminate analysis is a similar technique to multiple regression except that it is used for categorized data.…”

An Application of Multivariate Analysis in Modeling Students Placement in Nigerian Higher Institutions

“…Subsequent researches focused on not only on predicting student's placement through the use of performance, but also on other factors that might influence a student's performance in the school. Dyer et al (2002) and in identifying students at risk, that is identifying a student at risk of failure of the academic programme, because of the student's social background, status, religious inclination, race and other variables worth considering because of it's political and social implications in a multi cultural and heterogeneous society (Thomas et al, 1996). Pyryt (1986) used Discriminant analysis to illustrate how the technique can maximize the effectiveness and efficiency of screening procedures for identifying intellectually gifted children.…”