Analysis of the effect of course structure and pattern of usage on the efficacy of online/blended courses

Oosthuizen, Andries Cornelius

Analysis of the effect of course structure and pattern of usage on the efficacy of online/blended courses

Thesis / Dissertation

2024

Publisher

University of Cape Town

Department

Department of Statistical Sciences

Faculty

Faculty of Science

Abstract

Using the Sakai Learning Management System (LMS), this dissertation investigates the structure of course sites in blended and online courses at the University of Cape Town. Then, it evaluates the student interactions that this facilitates. The data selected focused on undergraduate courses in 2019. The student interactions with the tool selected for each site are compared to tool categories that indicate a good academic outcome. The analysis was structured to use four popular unsupervised learning algorithms (K-means, PAM, AGNES, and DIANA) on data sets that included the enrolled users and the tools accessible to students. The clValid package method was used to choose the optimal algorithm and cluster sizes. The findings show that most sites used the default tool selection, with almost half the courses adding outside tools and linking in lecture recordings. Sites with less enrolled students were shown to include more diffuse tools, which allow for more creative pedagogy. The majority of student interactions were for course development and delivery, followed by grading and assessment. Finally, most students utilised the LMS and accessed a high percentage of tools in each category. However, the analysis had certain limitations about the events tracked by the system and assumed a one-sided perspective as only the student interaction with the LMS was considered.

Keywords

statistical science

Reference:

Collections

Masters

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