Predicting Student Academic Performance

Engineering schools worldwide have a relatively high attrition rate. Typically, about 35% of the first-year students in various engineering programs do not make it to the second year. Of the remaining students, quite often they drop out or fail in their second or third year of studies. The purpose of this investigation is to identify the factors that serve as good indicators of whether a student will drop out or fail the program. In order to establish early warning indicators, principal component analysis is used to analyze, in the first instance, first-year engineering student academic records. These performance predictors, if identified, can then be used effectively to formulate corrective action plans to improve the attrition rate.