The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
The strengths, weaknesses, opportunities and threats of using social software in higher and further education teaching and learning
Open accessAbstract
Social software is increasingly being used in higher and further education to support teaching and learning processes. These applications provide students with social and cognitive stimulation and also add to the interaction between students and educators. However, in addition to the benefits the introduction of social software into a course environment can also have adverse implications on students, educators and the education institution as a whole, a phenomenon which has received much less attention in the literature. In this study we explore the various implications of introducing social software into a course environment in order to identify the associated benefits, but also the potential drawbacks. We draw on data from 20 social software initiatives in UK‐based higher and further education institutions to identify the diverse experiences and concerns of students and educators. The findings are presented in form of a SWOT analysis, which allows us to better understand the otherwise ambiguous implications of social software in terms of its strengths, weaknesses, opportunities and threats. From the analysis we have derived concrete recommendations for the use of social software as a teaching and learning tool.
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Metadata
- Authors
- Schroeder, A., Minocha, S., & Schneider, C.
- Venue
- Journal of Computer Assisted Learning
- Publisher
- Wiley
- Published
- 2010-05-13
- Volume
- 26
- Issue
- 3
- Pages
- 159-174
- ISSN
- 0266-4909 (ISSN-L)
- 1365-2729
- OpenAlex
- W1869813581
- Cited by
- 278
- References
- 29
- FWCI
- 61.44
- Type
- journal article
- Language
- en
- Open access
- green
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- Schroeder, A., Minocha, S., & Schneider, C. (2010). The strengths, weaknesses, opportunities and threats of using social software in higher and further education teaching and learning. Journal of Computer Assisted Learning. https://doi.org/10.1111/j.1365-2729.2010.00347.x
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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.
