The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Social presence in online discussions as a process predictor of academic performance
Open accessAbstract
With the steady development of online education and online learning environments, possibilities to support social interactions between students have advanced significantly. This study examined the relationship between indicators of social presence and academic performance. Social presence is defined as students' ability to engage socially with an online learning community. The results of a multiple regression analysis showed that certain indicators of social presence were significant predictors of final grades in a master's level computer science online course. Moreover, the study also revealed that teaching presence moderated the association between social presence and academic performance, indicating that a course design that increased the level of meaningful interactions between students had a significant impact on the development of social presence, and thus could positively affect students' academic performance. This is especially important in situations when discussions are introduced to promote the development of learning outcomes assessed in courses. Another implication of our results is that indicators of social presence can be used for early detection of students at risk of failing a course. Findings inform research and practice in the emerging field of learning analytics by prompting the opportunities to offer actionable insights into the reasons why certain students are lagging behind.
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Cites
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A Meta-Analysis of Three Types of Interaction Treatments in Distance Education
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Predicting academic performance: a systematic literature review
Hellas, A., Ihantola, P., Petersen, A., Ajanovski, V. V., Gutica, M., Hynninen, T., Knutas, A., Leinonen, J., Messom, C., & Liao, S. N. (2018) · Proceedings Companion of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education · doi:10.1145/3293881.3295783 · Cited by 355
Händel, M., Stephan, M., Gläser-Zikuda, M., Kopp, B., Bedenlier, S., & Ziegler, A. (2022) · Journal of Research on Technology in Education · doi:10.1080/15391523.2020.1846147 · Cited by 292
Effects of teacher role on student engagement in WeChat-Based online discussion learning
Xu, B., Chen, N.-S., & Chen, G. (2020) · Computers & Education · doi:10.1016/j.compedu.2020.103956 · Cited by 271
Bedenlier, S., Wunder, I., Gläser-Zikuda, M., Kammerl, R., Kopp, B., Ziegler, A., & Händel, M. (2021) · International Journal of Educational Research Open · doi:10.1016/j.ijedro.2021.100068 · Cited by 93
Archbell, K. A., & Coplan, R. J. (2022) · Journal of Emotional and Behavioral Disorders · doi:10.1177/10634266211060079 · Cited by 95
Metadata
- Authors
- Joksimović, S., Gašević, D., Kovanović, V., Riecke, B. E., & Hatala, M.
- Venue
- Journal of Computer Assisted Learning
- Publisher
- Wiley
- Published
- 2015-06-04
- Volume
- 31
- Issue
- 6
- Pages
- 638-654
- ISSN
- 0266-4909 (ISSN-L)
- 1365-2729
- OpenAlex
- W1504818606
- Cited by
- 278
- References
- 8
- FWCI
- 59.51
- Type
- journal article
- Language
- en
- Open access
- green
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
