The affinity space framework has proven useful for explaining and understanding teacher activity on social media platforms. In this study, we explore the ‘dark side’ of teacher affinity spaces by documenting a partisan teachers’ group on an alternative social media platform. We used a mix of a priori and emergent coding to analyse screenshots of posts and comments from a public teachers’ group and group administrators’ activity on the broader platform. Findings indicate that although the group administrators began with a focus on teachers, most participants were non-teachers with political (rather than professional) concerns about US education. Furthermore, administrators both freely engaged with political talking points in their activity outside the teachers’ group and allowed the broader platform culture—including conspiratorial thinking, explicit racism and out-group villainization—to seep in. We conclude by describing how these findings correspond with the key characteristics of an affinity space, including an overlapping of affinities, a lack of concern for professional qualifications, and influence from the broader platform. These findings provide an illustrative example of how teacher affinity spaces can drift from their stated intention within the larger platform context.

There is an abundance of scholarship documenting educators’ uses of for-profit social media platforms for professional learning, but little is known about how inauthentic accounts affect those experiences. We studied 83 state-sponsored accounts’ interactions with the teacher-focused #Edchat hashtag by analyzing their profiles, profiles of accounts they retweeted, and tweets they shared. We found no patterns of overt state interference in #Edchat; however, state-sponsored accounts amplified other inauthentic accounts, such as those focused on commercial, spam, and self-promoting #Edchat messages. Most state accounts used formulaic methods to create relatable account profiles that may go unnoticed by educators using the hashtag. These findings raise questions for educators and researchers about disinformation, anonymity, attention-seeking, and information glut in social media environments polluted by inauthentic amplification.

Teachers participate in professional learning activities to enhance their pedagogical knowledge and share best practices—and the increasing role of technologies in education, including social media, is shifting how this professional learning occurs. The COVID-19 pandemic provided an opportunity to consider the role of social media for professional learning. Using intensive longitudinal methods, we repeatedly surveyed 14 teachers’ use of social media both before and during the pandemic (N = 386 total responses). We found patterns in social media platforms uptake and their purposes, but teachers’ use of social media was largely idiosyncratic. Also, teachers demonstrated notable shifts in social media use after the pandemic started; multilevel models indicated that teachers were more likely to use social media to connect and share, especially, as well as learn and follow, compared with before the pandemic. Higher levels of COVID-19-related family stress were also associated with more use of social media to find materials.

Research on teachers’ use of social media has typically assumed that it is a) driven by a need for professional learning and b) best understood in terms of individual motivations. In this study, we use a dataset of nearly 600,000 tweets posted to one or more of 48 Regional Educational Twitter Hashtags associated with 44 U.S. states. To explore the influence of local contextual factors on hashtag- and account-level activity in these hashtags, we use an analytic approach heretofore uncommon in social media-focussed education research: generalised linear and multilevel modelling. At the hashtag level, higher numbers of teachers within a state, proportions of students receiving subsidised meals, student-to-teacher ratios, and amounts of state spending per child are associated with more activity within a regional hashtag; by contrast, more left-leaning state governments and citizenries are associated with less activity. At the account level, more experienced accounts and accounts in more right-leaning states contribute more tweets to these hashtags. These findings reinforce established understandings of Twitter as a site for teacher learning; however, they also underline the importance of acknowledging other important purposes of teachers’ Twitter use, including receiving emotional support and engaging in activism.

Twitter hashtags may serve as valuable means for teachers’ professional development. However, given the diversity of hashtag spaces and teacher needs, teachers must assess a given hashtag and compare it to their learning needs and preferences before determining whether it would be helpful. To support this reflection, I examine data associated with 60 Regional Educational Twitter Hashtags (RETHs) during the first six months of 2016 to begin describing the variety of teacher learning-focused Twitter spaces and make distinctions between them. My results indicate that these RETHs vary according to their relative focus on sharing, intimacy of personal connection, and volume of activity, each of which has implications for professional development. The dimensions resulting from this study may prove helpful for teachers, teacher educators, and hashtag coordinators.

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.

Twitter and other social media have assumed important places in many educators’ professional lives by hosting spaces where new kinds of collegial interactions can occur. However, such spaces can also attract unwelcome Twitter traffic that complicates researchers’ attempts to explore and understand educators’ professional social media experiences. In this article, we define various kinds of spam that we have identified in our research on educators’ uses of Twitter. After providing an overview of the concept of spam, we evaluate the advantages and disadvantages of different approaches to addressing the presence of spam in educator-focused Twitter spaces. Then we suggest practical, holistic metrics that can be employed to help identify spam. Through secondary analyses of our past research, we describe the use of such metrics to identify and deal with spam in three specific cases. Finally, we discuss implications of spam and these suggested methods for teacher educators, instructional designers and educational technology researchers.

Although researchers have discovered a great deal about who uses Twitter for educational purposes, what they post about, when they post and why they participate, there has so far been little work to explore where participants in educational Twitter contexts are located. In this paper, we establish a methodological foundation that can support the exploration of geographical issues in educational Twitter research. We surveyed 46 participants in one educational Twitter hashtag, #michED, to determine where they lived; we then compared these responses to results from three digital methods for geolocating Twitter users (human coding, machine coding and GPS coding) to explore these methods’ affordances and constraints. Human coding of Twitter profiles allowed us to analyze more participants with higher levels of accuracy but also has disadvantages compared to other digital—and traditional—methods. We discuss the additional insights obtained through geolocating #michED participants as well as considerations for using geolocation and other digital methods in educational research.

This paper examines the use of social media to foster community connections within the MSU Urban Science, Technology, Engineering, and Mathematics (STEM) program. We describe the strategies employed by the program and the technologies employed by instructors to provide support, build community, and showcase learning. We highlight three particular tools used to foster community within the program: Facebook, websites and blogs, and Twitter and then use trace data from Twitter to demonstrate how social media fostered community within the program. We conclude with a description of implications for how social media is used to support community for future research and practice.

Despite the growing popularity of digital teaching portfolios, research has remained focused on outcomes associated with making digital teaching portfolios instead of examining the ways in which they can effectively assess what teachers know, especially when it comes to educational technology. One barrier to using portfolios as a means of assessing teachers’ knowledge of technology is the lack of a guiding framework for characterizing teachers’ technology knowledge. In this paper, we propose that the Technological Pedagogical Content Knowledge (TPACK) framework is well-suited to study the knowledge (including technological knowledge) teachers represent in their digital teaching portfolios. We exemplify how the TPACK framework can guide a content analysis of digital teaching portfolios by analyzing 589 online portfolios created by teachers as the culminating assessment in their master’s studies. We conclude that the TPACK framework is helpful for analyzing the types of technological knowledge teachers may represent in portfolios but also acknowledge several important challenges.

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.

Affinity spaces are digital or physical spaces in which participants interact with one another around content of shared interest and through a common portal (or platform). Among teachers, some of the largest affinity spaces may be those organized around hashtags on Twitter: These spaces are public, largely unmoderated, and thriving, yet very little is known about them, especially those based in geographical areas such as American states. This paper examines these potential affinity spaces by providing the first large-scale study of them in the form of an examination of 47 State Educational Twitter Hashtags (SETHs). Collecting over 550,000 tweets over 6 months, our analysis focused on who is participating in SETHs, how active participants are, and when participation occurred. We found support for two of Gee’s tenets of affinity spaces, in particular many interactions through a shared portal. Though the content of tweets were not the focus, this study’s findings lend support to efforts to identify which particular SETHs will be best suited to subsequent analysis of their content and what times subsequent analysis might most productively focus on. We discuss implications for how we conceive of teacher professional development and suggest directions for future research focused on the content of tweets associated with SETHs.

Twitter is increasingly accepted as an important educational technology and has been shown to serve a range of purposes. In fact, this variety suggests that Twitter has the potential to serve as a foundational technology: one capable of supporting teachers’ learning across multiple formal and informal contexts. To explore this possibility, we examined the purposes that Twitter serves in one educational technology graduate program. We collected over 9000 tweets containing any of 12 program-related hashtags and coded a sample of them to describe the purposes they served. This resulted in six themes: contribute to disciplinary conversation, engage with disciplinary conversation, build community, make connections with other communities, ask for and provide support, and unclear or irrelevant purpose. These themes—and the varied contexts they were associated with—suggest that Twitter serves as a foundational technology in this program and has the potential to do so in other educational communities.