I recently published a review paper with Bernadette Mercieca and Paul Mercieca in BERA’s journal Review of Education. This paper looks at how 96 different studies by researchers all over the world have analysed teacher activity within social network sites. These are sites like Facebook, Twitter, Instagram, and many others. What it shows is that there are serious and systemic methodological concerns in how researchers are studying teachers within these platforms.
You can read the full paper online here or access the article directly on my eprints.
The essence of the findings are that any researchers looking at teachers within social network sites should:
- Report on the specific qualities of the groups of teachers that they are studying, including its size, origins, privacy, thematic focus, regional focus, and platform
- Consider re-using existing frameworks for analysis (such as the ACAD framework of Goodyear & Carvalho, 2014)
- Consider re-using or building upon existing coding schemes or research instruments and publish such schemes and instruments with their work to permit them to be re-used in future (a description of instruments that might be re-used are included in the paper)
- Consider the sampling methods adopted and ensure that sampling is described in detail with all limitations made salient, with particular attention being given to self-selection and to recruitment within the platforms being studied.
- Consider the claims being made and ensure that they are specific with respect to the population that they apply to and the conditions under which they are likely to apply
Of all of these, number (4) is the biggest concern in my opinion. Many studies use self-selection during recruitment; where that self-selection is taking place within a group that is already self-selected by being on that platform. As in, say, teachers using a Twitter hashtag are only a small proportion of all teachers, and then to just sample the teachers who respond to your survey really doesn’t say much about the population of all teachers. Yet many papers seem not to take care with the claims (point (5) here).
The paper also includes a summary of all of the key themes that are addressed with respect to teachers in social network sites (or social media as people sometimes refer to it still). This is Figure 2 within the paper. It shows an abstract model of relationships between domains of change, observable teacher behaviours (within social network sites), and the outcomes that have been hypothesised as resulting from these behaviours. Arrows in this figure do not presume causality; they represent relationships that may come to be understood through future research
This provides a useful map for those studying teachers in social network sites to place their work within a broader framework.
There is also a useful appendix in the paper that lists all 96 studies as a database, with information about each one. This will be useful for any researchers conducting similar reviews in future.
References
Goodyear, P., & Carvalho, L. (2014). Framing the analysis of learning network architectures. In The Architecture of Productive Learning Networks (pp. 66-88). Routledge.
Kelly, N., Mercieca, B., & Mercieca, P. (2021). Studying teachers in social network sites: a review of methods. Review of Education, 9(3), https://doi.org/10.1002/rev3.3272