A comparison of different study load classifications and their association to student performance: an exploratory study

Purpose – The purpose of this paper is to investigate the alternative study load measures (dichotomous full-time/part-time classification and the number of units enrolled) and their association to student performance by using student data from a final year accounting unit in a large Australian university.
Design/methodology/approach – Using regression analysis, the authors compare the two measures to ascertain the explanatory power of the two approaches in explaining student performance.
Findings – A positive association is found between study loads and student performance when using the “number of units enrolled” measure. This relationship was not found when the dichotomous measure (full-time vs part-time) was used. The results suggest that a scaled measure of study loads is a better measure compared to a binary (dichotomous) measure.
Research limitations/implications – The study will assist future researchers to better control for study loads, and also to gain a better understanding of the association between study loads and student performance. This may possibly assist educational institutions and academics to use a more appropriate pedagogical design in the structure of courses when determining study load allocations across the different cohorts.
Practical implications – This study will help in methodology of future researchers controlling for study loads and student performance.
Originality/value – The study adds to existing literature by providing an alternate study load measure in methodology for controlling for student performance.