Challenges of student selection: Predicting academic performance

Finding accurate predictors of tertiary academic performance, specifically for disadvantaged students, is essential because of budget constraints and the need of the labour market to address employment equity. Increased retention, throughput and decreased dropout rates are vital. When making admission decisions, the under preparedness of students necessitates that their potential cognitive abilities should be assessed rather than their current abilities. In predicting their academic performance, it is argued that conventional psychometric tests are less suitable for the selection of students from disadvantaged backgrounds, because they are a static measure of current abilities which gives no indication of the student's potential to learn when in an optimum environment. The predictive validity of the Potential Index Battery, the Learning Potential Computerised Adaptive Test and schoolleaving results in selection, were determined by calculating the correlation of these measures with academic performance over the full duration of the students' studies. Statistically significant correlations were found, thus indicating that the learning potential test had higher predictive powers than static measures of cognitive ability and school-leaving results, in predicting future academic performance. South African Journal of Higher Education Vol. 20(4) 2006: pp.547-56