OnDiscuss: An Epistemic Network Analysis Learning Analytics Visualization Tool for Evaluating Asynchronous Online Discussions
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866913490378162176 |
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| author | Luther, Yanye Moraes, Marcia Ghosh, Sudipto Folkestad, James |
| author_facet | Luther, Yanye Moraes, Marcia Ghosh, Sudipto Folkestad, James |
| contents | Asynchronous online discussions are common assignments in both hybrid and online courses to promote critical thinking and collaboration among students. However, the evaluation of these assignments can require considerable time and effort from instructors. We created OnDiscuss, a learning analytics visualization tool for instructors that utilizes text mining algorithms and Epistemic Network Analysis (ENA) to generate visualizations of student discussion data. Text mining is used to generate an initial codebook for the instructor as well as automatically code the data. This tool allows instructors to edit their codebook and then dynamically view the resulting ENA networks for the entire class and individual students. Through empirical investigation, we assess this tool's effectiveness to help instructors in analyzing asynchronous online discussion assignments. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2409_00051 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | OnDiscuss: An Epistemic Network Analysis Learning Analytics Visualization Tool for Evaluating Asynchronous Online Discussions Luther, Yanye Moraes, Marcia Ghosh, Sudipto Folkestad, James Human-Computer Interaction Computers and Society Asynchronous online discussions are common assignments in both hybrid and online courses to promote critical thinking and collaboration among students. However, the evaluation of these assignments can require considerable time and effort from instructors. We created OnDiscuss, a learning analytics visualization tool for instructors that utilizes text mining algorithms and Epistemic Network Analysis (ENA) to generate visualizations of student discussion data. Text mining is used to generate an initial codebook for the instructor as well as automatically code the data. This tool allows instructors to edit their codebook and then dynamically view the resulting ENA networks for the entire class and individual students. Through empirical investigation, we assess this tool's effectiveness to help instructors in analyzing asynchronous online discussion assignments. |
| title | OnDiscuss: An Epistemic Network Analysis Learning Analytics Visualization Tool for Evaluating Asynchronous Online Discussions |
| topic | Human-Computer Interaction Computers and Society |
| url | https://arxiv.org/abs/2409.00051 |