文章基本信息

标题：Prediction of Students’ Performances Using Course Analytics Data: A Case of Water Engineering Course at the University of South Australia
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作者：Faisal Ahammed ; Elizabeth Smith
期刊名称：Education Sciences
电子版ISSN：2227-7102
出版年度：2019
卷号：9
期号：3
页码：245-259
DOI：10.3390/educsci9030245
出版社：MDPI Publishing
摘要：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.
关键词：course analytics; learn-online site login; students’ performances; statistical tests course analytics ; learn-online site login ; students’ performances ; statistical tests