28 Days Later: Twitter Hashtags as “Just in Time” Teacher Professional Development
Researchers have argued that Twitter has potential to support high-quality professional development (PD) that can respond to teachers’ questions and concerns just in time and “on the spot.” Yet, very little attention has been paid to instances where Twitter has made just-in-time learning possible. In this paper, we examine one instance of timely professional development on Twitter, in which 3,598 users used an educational hashtag—#educattentats—to create a temporary affinity space supporting French teachers preparing to discuss recent terrorist attacks with their students. We describe this just-in-time PD by focusing on participants and modes of participation, the spread of the hashtag in its first hours and the growth and eventual decline of the hashtag over the course of 28 days. The results of this study suggest that #educattentats served effectively as just-in-time professional development for teachers. Implications for research and practice are discussed.
KeywordsAffinity spaces Professional development Social learning Social media Social networking sites Teacher learning Twitter
We would like to thank Josh Rosenberg and Sarah Gretter for their contributions to and advice for our analysis.
- Anderson, S. (2012). A brief history of #edchat [Blog post]. Retrieved from http://blog.web20classroom.org/2012/03/brief-history-of-edchat.html.
- Carpenter, J. (2015). Preservice teachers’ microblogging: professional development via Twitter. Contemporary Issues in Technology and Teacher Education, 15, 209–234.Google Scholar
- Darling-Hammond, L., & McLaughlin, M. W. (1995). Policies that support professional development in an era of reform. Phi Delta Kappan, 76, 597–604.Google Scholar
- Gee, J. P. (2004). Situated language and learning: A critique of traditional schooling. New York: Routledge.Google Scholar
- Greeno, J., Collins, A., & Resnick, L. (1996). Cognition and learning. In D. Berliner & R. Calfee (Eds.), Handbook of educational psychology (pp. 15–46). New York: Macmillan.Google Scholar
- Hawksey, M. (2014). Need a better Twitter Archiving Google Sheet? TAGS v6.0 is here! [Blog post]. Retrieved from https://mashe.hawksey.info/2014/10/need-a-better-twitter-archiving-google-sheet-tags-v6-0-is-here/.
- Munzert, S., Rubba, C., Meißner, P., & Nyhuis, D. (2015). Automated data collection with R: A practical guide to web scraping and text mining. West Sussex: Wiley.Google Scholar
- Remler, D. K., & Van Ryzin, G. G. (2011). Research methods in practice: Strategies for description and causation. Thousand Oaks: SAGE Publications.Google Scholar
- Rosenberg, J. M., Greenhalgh, S. P., Koehler, M. J., Akcaoglu, M., & Hamilton, E. (2016). An investigation of State Educational Twitter Hashtags (SETHs) as affinity spaces. E-Learning and Digital Media, 13, 24–44. doi: 10.1177/2042753016672351.
- Saldaña, J. (2015). The coding manual for qualitative researchers. Thousand Oaks: SAGE Publications.Google Scholar
- Snee, H., Hine, C., Morey, Y., Roberts, S., & Watson, H. (2016). Digital methods as mainstream methodology: An introduction. In H. Snee, C. Hine, Y. Morey, S. Roberts, & H. Watson (Eds.), Digital methods for social science: An interdisciplinary guide to research innovation (pp. 1–11). New York: Palgrave Macmillan.Google Scholar
- Welser, H. T., Smith, M., Fisher, D., & Gleave, E. (2008). Distilling digital traces: Computational social science approaches to studying the internet. In N. Fielding, R. M. Lee, & G. Blank (Eds.), The SAGE handbook of online research methods (pp. 116–141). Thousand Oaks: SAGE Publications, Ltd.CrossRefGoogle Scholar