This chapter explores the strengths and drawbacks of using digital traces of interactions on social media as a measure of educators’ professional networks. We first review prior research on how perceived (self-reported) and observed (via digital trace) networks compare. We then leverage a unique data set of both teachers' (n = 120 respondents) perceptions of their professional network associated with the #NGSSchat X/Twitter hashtag for science educators, and observed measures of the interactions of teachers (n = 10,785 users) in the same network. Based on these two data sources, we compare the size of the network, centrality measures, and alignment of self-reported interactions. These show that the network on Twitter is larger and has different central individuals than those identified through the survey results. This study offers insights into the use of digital data in studying teachers' social networks and provides practical implications for researchers studying teachers' digital networks. Specifically, we recommend that analysts carefully describe and justify their use of individual methods and consider using multiple methods.

Some argue that support for the social safety net in the United States is influenced by beliefs about the beneficiaries' race. Information treatments have the potential to change these beliefs, but for them to be policy relevant, their effects must last beyond the intervention. Our findings from two parallel experiments that exploit the different racialized histories of welfare and unemployment insurance indicate that racial beliefs do predict stated support for the racially stigmatized welfare program but not for the less stigmatized unemployment program. We also find that these beliefs are stable if uncorrected and that they can be persistently corrected.

This scoping review summarizes and analyzes 82 empirical articles on preservice teacher (PST) study abroad of at least three weeks in duration and featuring an education field experience. Our analysis found that most studies focused on cross-cultural/intercultural awareness, understanding, competence, and/or communication, and included small sample sizes of undergraduate PSTs. Findings suggested that study abroad programs with field experiences facilitate growth in PSTs’ knowledge, skills, and dispositions. Limitations to PST gains were apparent, suggesting that study abroad experiences run the risk of reinforcing stereotypes and ethnocentrism. We identify gaps in the literature and offer recommendations for future research.

Before pre-service teachers (PSTs) enter educator preparation programs, their experiences as K-12 students shape their understanding of teaching. Additionally, many aspiring teachers are exposed via social media to ideas, resources, and narratives about teachers and teaching. To help explore and conceptualize how social media may be adding to PSTs' knowledge and expectations of teaching, we interviewed 28 PSTs about factors, experiences, and role models contributing to their understanding of teaching. Participants reported having learned about teaching through social media and demonstrated some awareness of the complexities and challenges of such learning. Most PSTs also valued content shared by teachers on social media but did not see these teachers as role models.

There is a large literature evaluating the dual process model of cognition, including the biases and heuristics it implies. However, our understanding of what causes effortful thinking remains incomplete. To advance this literature, we focus on what triggers decision-makers to switch from the intuitive process (System 1) to the more deliberative process (System 2). We examine how the framing of incentives (gains versus losses) influences decision processing. To evaluate this, we design experiments based on a task developed to distinguish between intuitive and deliberative thinking. Replicating previous research, we find that losses elicit more cognitive effort. Most importantly, we also find that losses differentially reduce the incidence of intuitive answers, consistent with triggering a shift between these modes of cognition. We find substantial heterogeneity in these effects, with young men being much more responsive to the loss framing. To complement these findings, we provide robustness tests of our results using aggregated data, the imposition of a constraint to hinder the activation of System 2, and an analysis of incorrect, but unintuitive, answers to inform hybrid models of choice.

Fundraising for non-profit organizations (NPOs) often involves converting in-kind donations into cash, commonly through charity auctions. However, little attention has been paid to the revenue distributions these mechanisms generate, an obvious concern for risk-averse NPOs deciding on a fundraising strategy. This paper introduces a theoretical framework that evaluates the first two moments of the revenue distributions accruing to ten auction formats under conditions that permit endogenous bidder participation. The resulting "revenue frontier" generated by these mechanisms reveals a robust and sizeable mean-variance tradeoff that NPOs should consider when selecting which mechanism(s) to employ. We test the model's predictions for each auction format using both laboratory and field experiments and find evidence of a substantial (and similar) tradeoff in each setting. Additionally, we show how bidder participation can modulate an NPO's risk exposure, conditional on the auction formats selected. These results offer important insights into how NPOs might optimize their fundraising strategies through methods of mechanism diversification.

Self-directed educator professional learning is commonplace, and such activities increasingly span multiple digital spaces and formats, and blur boundaries between online and offline. In this exploratory research, we analyze the case of the #CharlasEducativas, a dynamic professional learning ecosystem that began in 2020 and is based in Spain. We describe the platforms, modalities, and activities that comprised the #CharlasEducativas from 2020–2023, and how these different elements combine to create a multiplatform learning ecosystem. Relying upon multiple data sources, we also analyze the topics and content associated with various components of this unique ecosystem, and share participant perceptions of the #CharlasEducativas. Although the ecosystem was first developed relying mostly on YouTube and X/Twitter, the #CharlasEducativas have evolved over time to include additional platforms, and even in-person events, with different spaces functioning in overlapping and distinct ways. These spaces have been employed in synchronous and asynchronous ways, using text, images, voice, and visuals to discuss and share information on a wide array of education topics. Many participants reported perceiving the #CharlasEducativas as a space of learning and community building, and credited this learning and community with sparking reflection upon and changes in their own teaching practices. We discuss how the #CharlasEducativas reflect opportunities and challenges of contemporary educator professional learning in the context of ubiquitous social media platforms. Finally, we define implications for research and practice, highlighting the need to advance understanding of educators’ multiplatform professional learning activities.

Purpose The purpose of this conceptual paper is to describe how the affinity space concept has been used to frame learning via social media, and call for and discuss a refresh of the affinity space concept to accommodate changes in social media platforms and algorithms. Design/methodology/approach Guided by a sociocultural perspective, this paper reviews and discusses some ways the affinity space concept has been used to frame studies across various contexts, its benefits and disadvantages and how it has already evolved. It then calls for and describes a refresh of the affinity space concept. Findings Although conceptualized 20 years ago, the affinity space concept remains relevant to understanding social media use for learning. However, a refresh is needed to accommodate how platforms have changed, algorithms’ evolving role in social media participation and how these technologies influence users’ interactions and experiences. This paper offers three perspectives to expand the affinity space concept’s usefulness in an increasingly platformized and algorithmically mediated world. Practical implications This paper underscores the importance of algorithmic literacy for learners and educators, as well as regulations and guidance for social media platforms. Originality/value This conceptual paper revisits and updates a widely utilized conceptual framing with consideration for how social media platform design and algorithms impact interactions and shape user experiences.

Asking questions on social media acts as a stimulus for professional learning among educators, while the answers can offer them valuable resources. Framed by the concept of digital social support and using a cross-cultural comparative approach, we investigate what type of digital social support educators seek when using educational social media spaces, and what they receive from other users who answer their questions. Analyzing 2,274 tweets and 2,020 replies from two hashtags popular among German and US teachers, #twlz and #teachertwitter, we find that educators mainly seek instrumental support (e.g. materials). Yet what is being sought influences the likelihood of getting the desired response, not the user's characteristics. Differences emerge between the two hashtags in the kinds of support educators seek and the way educators respond to requests. The findings highlight the need for educators to possess digital competencies to fully utilize social media spaces.

Since Twitter’s 2006 inception, educators have used the platform, more recently rebranded as X, for multiple purposes related to teaching and learning. Social media such as X have proven to be flexible sources of just-in-time learning for many educators across sectors. Education-related X hashtags and the synchronous and asynchronous chats associated with many of them have played host to various kinds of interactions amongst participants. Educators access ideas, share resources and connect with colleagues. Chats related to hashtags can function as Social Learning Spaces, where members drive the learning agenda and learning is rooted in mutual engagement. However, little is formally known about the value participants gain from being involved in these chats and how they contribute to their professional learning. They remain a relatively unrecognised form of professional learning. This qualitative study sought to explore participants’ experiences and determine what learning they gained from their chat involvement. A thematic analysis revealed participants were in two main categories: those who used X chats to gain ideas for teaching, and more experienced teachers who valued chats for their broad discussion of theory, issues, and challenges around their practice. These findings provide insight into how such forms of professional learning should be recognised and validated in educational contexts.

This study investigated the impact of a course-based community asset mapping (CAM) project on undergraduate students' capacity for identifying and understanding assets within communities surrounding specific schools. The mapping project was grounded in the literature on culturally sustaining pedagogy and experiential education and involved teacher education students (n = 45) collaborating to complete and report on an analysis of local community assets. Findings indicated participants gained improved knowledge and competence regarding CAM, were able to provide more accurate and detailed explanations of assets and the asset mapping process, and were able to identify various assets available to PK-12 students and families in particular communities within the local school district. The discussion highlights participants' success in inventorying physical, tangible assets, and notes where they fell short of recognizing other assets. We also discuss how coursework could have better supported the project and could have allowed the potential of CAM to be more fully realized. The conclusion addresses implications for teacher preparation, particularly for connecting candidates with communities and for the implementation of assignments similar to the community asset mapping project studied herein.

Digital technologies permeate modern life, and schools are accordingly expected to help students develop related knowledge and skills. As a result, educators' professional digital competence (PDC) has received substantial attention from school leaders, policymakers, teacher educators, and researchers. Theory and prior research suggest that educators' PDC does not solely determine their technology use, with contextual factors, such as competing curricular demands and access to technology, influencing technology implementation and ongoing PDC development. While some prior research has addressed how PK-12 teachers' contexts shape their digital technology use, few studies have explored similar matters with respect to teacher educators. Drawing on an established set of teacher educator technology competencies, we report results from an international survey of 336 teacher educators regarding their self-reported PDC and its development and enactment. Using qualitative coding, exploratory and confirmatory factor analysis, and quantitative analysis, we find that teacher educators develop and enact their competencies in various ways including through informal endeavours as well as formal, institutionally supported, and/or led activities. Three types of assets and barriers (access, leadership, personal characteristics) present differently for participants in different contexts. These findings have implications for how institutions support teacher educators' PDC development and technology integration in various settings.

Measuring the social preferences of economic agents using experiments has become common place. This process, while incentive compatible, is costly and time consuming, making it infeasible in many settings. We combine standard altruism and warm glow choice experiments with a battery of candidate survey questions to construct behaviorally-validated questionnaires. We use machine learning to create parsimonious 3-question modules that reliably replicate existing results on general altruism and provide an alternative method for collecting warm glow preferences.

This article analyzes the relationship between self-regulated learning (SRL) and personal learning environments (PLE) in light of the educational academic literature of the decade 2010-2020. This study uses a systematized literature review followed by a qualitative analysis of the most cited literature to establish a narrative that highlights and deconstructs the close relationship between learners' SRL skills, and their capacity to develop and refine their PLE. For this purpose, in this analysis we explore (1) the presence of the PLE concept in the 200 most referenced papers published on SRL, and (2) the relationship between the two concepts, as they appear in the 20 most frequently cited articles that include both of them. Results show that SRL is linked to an educational and mixed perspective on the PLE concept, and that a variety of designs and platforms exist for teaching strategies linking SRL and PLE in educational practices. In-depth analysis suggests a series of features that reveal the influence of SRL in the PLE concept. Conclusions address recommendations for further work to explore these features and the manner in which they can extend the features of the relationship between PLE and SRL.

The purpose of this mixed methods, multi-year study was to explore aspects of a virtual international literacies project, the Global Read Aloud, that promoted students' multiple literacies. Guided by theories of critical, digital, and global literacies, we analyzed survey (N = 436) and interview (N = 21) data from K-12 literacy educators. Data revealed that educators perceived GRA-related benefits of virtual collaboration for digital literacies learning, of reading quality multicultural literature, and of teaching critical literacies as foundational to global meaning making. The results of this study contribute teachers' voices to discussions on the importance of developing critical, digital, and global literacies in this interconnected world. Data suggest that using shared readings and virtual collaboration can foster a community of readers, locally and globally, that create possibilities for students to experience and use literacies as a part of participating in authentic global meaning making.

TeachersPayTeachers.com (TpT) is an influential online education resource marketplace where users download, buy, and sell education content. How and why educators use platforms like TpT has received only limited scholarly attention. This research therefore addresses a gap in the literature by exploring educators' (N=1359) self-reported uses and perceptions of TpT. Participants reported intensive and multifaceted TpT use, in particular to address curriculum gaps and time pressures. Most respondents perceived TpT content to be of high quality, but many also noted challenges with TpT. We discuss implications related to education resource production, distribution, and consumption in a digital era.

This paper extends the literature on structural estimation of social preferences to account for the desire to adhere to social norms and hide one's true intentions via moral wiggle room. We conduct an experiment to test whether accounting for normatively appropriate behavior allows us to distinguish between preference types who care about outcomes versus adhering to social norms and whether the introduction of moral wiggle room undermines the stability of social preference estimates. We find that social preference estimates are remarkably robust to the inclusion of moral wiggle room. However, the representative agent is strongly motivated by norms and failing to account for this motive in our model causes us to overestimate how much agents care about helping those who are worse off. Using finite mixture models to endogenously identify latent preference types, we replicate previous work finding that the majority of subjects can be classified as strong or moderate altruists when normative concerns are not considered. Accounting for the normative appropriateness of decisions when categorizing participants, however, reveals different motives across types: strong altruists are only marginally concerned with norms while the moderate altruists are highly sensitive to them and, once norms are taken into account, don't care at all about the outcomes of others. Our results thus recast the prior findings in a new light. Rather than the two most common types being strong altruists and moderate altruists, we find that they are better described as strong altruists and norm followers.