Prediction of Students’ Performances Using Course Analytics Data: A Case of Water Engineering Course at the University of South Australia

An association between students’ learn-online engagement and academic performance was investigated for a third-year Water Resources Systems Design course at the University of South Australia in 2017. As the patterns of data were non-parametric, Mann-Whitney and Kruskal-Wallis tests were performed using SPSS. It was revealed from the test results that distributions of students’ logins to learn-online site for all categories and sub-categories including gender, international/domestic students and grades were almost similar. Therefore, it is relatively unrealistic to use lean-online engagement data to predict students’ performances. A correlation test was further performed to validate the hypothesis testing results and a weak relationship (Pearson’s r = 0.29) between login to learn-online site and grade was observed. The smaller F ratios of one way ANOVA also validated the test results. Mann-Whitney and Kruskal-Wallis tests can be applied to course analytics data for face-to-face and online courses to understand a better picture about the uses of learn-online engagement data.