Identifying multiple learning spaces within a single teacher-focused Twitter hashtag. (April 2020)

• Record Type: Journal Article
• Authors: Greenhalgh, Spencer P.; Rosenberg, Joshua M.; Staudt Willet, K. Bret; Koehler, Matthew J.; Akcaoglu, Mete
• Is Part Of: Computers & education. Volume 148(2020)
• Publication Date: 2020-04
• Subjects: social media -- teacher professional learning -- Twitter; Education -- Data processing -- Periodicals; Education -- Periodicals; Computers -- Periodicals; Computer-Assisted Instruction -- Periodicals; Éducation -- Informatique -- Périodiques; Electronic journals; 370.285
• DOI: 10.1016/j.compedu.2020.103809
• Languages: English
• ISSNs: 0360-1315

Abstract

Abstract: The existing work on teacher-focused Twitter hashtags typically frames each hashtag as a single, unified phenomenon, thereby collapsing or erasing differences between them (and any resulting implications for learning). In this study, we conceived of teacher-focused hashtags as affinity spaces potentially containing subspaces distinguished by synchronous chats and other, asynchronous communication. We used computational methods to explore how participation differed in terms of content, interactions, and portals between these contexts within the #michED hashtag used by Michigan teachers. During the 2015–2016 academic year, #michED saw more non-chat activity than chat activity, and most participants only engaged in one mode of activity or the other. Participation during chats was associated with more replying as well as more socially-, affectively-, and cognitively-related content, suggesting a focus on social interaction. In contrast, non-chat participation was associated with more retweeting, mentioning, hyperlinks, and hashtags, suggesting a focus on content dissemination. These results suggest that different affinity spaces—and different literacy practices—may exist within the same hashtag to support different objectives. Teachers, teacher educators, and researchers should therefore be careful to make these distinctions when considering Twitter as a learning technology for teachers. Highlights: Chat and non-chat communication in #michED significantly differ. Chat-related communication appears to better support social interaction. Chat-unrelated communication appears to better support content dissemination. These different uses of #michED may be understood as distinct learning spaces.