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Direct linkConijn, R.; Van den Beemt, A.; Cuijpers, P. – Journal of Computer Assisted Learning, 2018
Predicting student performance is a major tool in learning analytics. This study aims to identify how different measures of massive open online course (MOOC) data can be used to identify points of improvement in MOOCs. In the context of MOOCs, student performance is often defined as course completion. However, students could have other learning…
Descriptors: Predictor Variables, Academic Achievement, Blended Learning, Online Courses
Arbaugh, J. B. – Journal of Computer Assisted Learning, 2014
Considering the increasingly challenging resource environments in many business schools, this study examined whether course technologies, learner behaviors or instructor behaviors best predict online course outcomes so that administrators and support personnel can prioritize their efforts and investments. Based on reviewing prior online and…
Descriptors: Online Courses, Educational Technology, Technology Uses in Education, Hypothesis Testing
Hwang, A.; Arbaugh, J. B. – Journal of Computer Assisted Learning, 2009
Emerging research has revealed the impact of electronic media usage on student outcomes, such as satisfaction and reported learning efficacy. However, little is known of its impact on measurable knowledge acquisition. Results from this study showed that participation on discussion topics through Blackboard, an electronic discussion forum,…
Descriptors: Context Effect, Electronic Publishing, Student Attitudes, Satisfaction
