ERIC Number: EJ1231070
Record Type: Journal
Publication Date: 2019
Pages: 15
Abstractor: As Provided
ISBN: N/A
ISSN: EISSN-2227-7102
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Prediction of Students' Performances Using Course Analytics Data: A Case of Water Engineering Course at the University of South Australia
Ahammed, Faisal; Smith, Elizabeth
Education Sciences, v9 Article 245 2019
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.
Descriptors: Foreign Countries, Water, Engineering Education, Academic Achievement, Prediction, Learning Analytics, Learner Engagement, Undergraduate Students, Civil Engineering, Electronic Learning
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Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
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Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Australia
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