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

This study investigates 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.

Using regression analysis, we compare the two measures to ascertain the explanatory power of the two approaches in explaining student performance.

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 versus part-time) was used. The results suggest that a scaled measure of study loads is a better measure compared to a binary (dichotomous) measure.

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.

This study will help in methodology of future researchers controlling for study loads and student performance.

The study adds to existing literature by providing an alternate study load measure in methodology for controlling for student performance.