Guest editorial: Introduction to the special issue – learning with social media in an algorithmic age: opportunities and challenges for education
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Bibliographic record
Abstract
Social media platforms have taken up central roles in modern life in the last two decades and have been found in a range of scenarios and contexts to serve a mediating and facilitating role in both incidental and purposeful learning (Greenhow et al., 2020; Lu and Lee, 2019; Woodford et al., 2023). Over the years, these platforms have increasingly relied upon artificial intelligence (AI) and machine learning to provide users with curated content and connections. Social media algorithms can amplify the spread of information that is accurate or inaccurate, sorting and ranking content at a speed and scale impossible for humans alone. These algorithms can expand, disrupt, and constrain how, when, where and from whom people learn, raising both opportunities and challenges for education.Meanwhile, recent disruptions and upheavals in education related to the COVID-19 pandemic (e.g. emergency remote teaching; Reynolds and Chu, 2020; Reynolds et al., 2022) as well as technology advancements such as increasingly sophisticated large language models, chatbots and/or generative AI, and problems of mis- and dis-information (Agosto and Oltmann, 2022), have triggered a re-imagining of what “learning” and “schooling” should look like, where these activities should occur and how the wider socio-technical contexts surrounding schooling and learning influence education (Akgun and Greenhow, 2022; Greenhow and Chapman, 2020; Greenhow and Galvin, 2020; Greenhow et al., 2022).For this special issue, we invited articles addressing learning and teaching with social media − whether required, invited, or self-directed learning − in settings spanning primary and secondary schooling (K-12), university education and professional learning, as well as informal spaces of learning such as libraries, museums and after-school programs, and among learners and publics of all ages. We sought articles that addressed conceptual, critical and empirical issues relevant to learning and teaching with social media in an age of enhanced user profiling and algorithms.Social media platform phenomena encapsulate many possibilities and perils in this present moment, and studying the intersection of learning and education with social media has strong merit and significance. These platforms have extended the scope, settings and nature of how teachers and students learn and communicate beyond boundaries of place, space, time and roles (Carpenter et al., 2024; Chapman and Greenhow, 2021; Galvin and Greenhow, 2020; Greenhow et al., 2021a, 2021b, 2023; Marich et al., 2021). Social media platforms have shown the capacity to facilitate just-in-time learning (Greenhalgh and Koehler, 2017; Li and Greenhow, 2015) across geographic boundaries (Greenhow et al., 2023; Staudt Willet, 2024) and increase engagement through enhanced user profiling as well as AI-powered algorithms. These affordances, in turn, may affect how students perceive their teachers, with teachers’ self-disclosure on social media being linked to students’ perceptions of their teachers’ credibility (Mazer et al., 2009). However, administrators are not always supportive of teachers’ social media use (Nochumson, 2021). Even still, social media can create alternative spaces outside of schools that allow student−teacher and teacher−administrator relationships to be free from typical hierarchical arrangements − for example where teachers can ask work-related questions without fear of reprisal (Carpenter and Staudt Willet, 2021; Staudt Willet, 2024).On the other hand, the same algorithms and data uses that potentially boost engagement for learning may also change the nature of learning processes, and teaching norms and practices, such as increasing expectations for teachers and learners to be constantly paying attention to platform activity (Fox and Bird, 2017; Selwyn et al., 2017; Staudt Willet, 2024), promoting themselves (Carpenter et al., 2022; Staudt Willet, 2019) and vetting and curating content (Archambault et al., 2021).These are just a few contextual concerns for teaching and learning that social media phenomena of today raise. On the whole, further investigation is required at all levels of education (primary through postsecondary education and professional learning) and as learners relate to design and uses of information and digital learning innovations. The evolving knowledge society and the emergence of information and communication technologies in our lives present complex challenges to educators and policymakers worldwide (Krutka et al., 2019). Education requires adjustments to these changes in learning and teaching, in the shattering of context boundaries that occurs in these platform and interface uses, and in the new meaning and momentum that they provide in advancing newly emerging educational paradigms.The scope of this special issue is broad, addressing teaching and learning with social media among learners and publics of all ages − whether required, invited, or self-directed learning − in settings spanning primary and secondary schooling (K-12), university education and professional learning, as well as informal and self-directed spaces of learning such as education-focused subreddits, and affinity spaces. This special issue offers a strong set of high-quality articles that address conceptual, critical, empirical and theoretical issues relevant to learning and teaching with social media in an age of enhanced user profiling and algorithms.This special double issue of Information and Learning Sciences, “Learning with social media in an algorithmic age: Opportunities and challenges for education,” is comprised of 12 articles, including one conceptual paper and 11 empirical articles. The articles address a range of social media platforms (i.e. YouTube, TikTok, Instagram, Facebook, X/Twitter, Reddit). Four articles address social media broadly. The empirical articles were based on studies conducted in the USA, Brazil and Spain. Moreover, the papers embrace a variety of theoretical perspectives, including socio-ecological learning theory, constructivism, connectivism, emergent collective sensemaking, affinity spaces, psychological well-being, technoskepticism and culturally relevant pedagogy. Of the empirical papers, eight employ a qualitative approach, one article adopts a quantitative design, one is a mixed-methods study and one article employs a technological audit. The majority of papers address informal learning with social media. Table 1 provides summary information for each of the 13 articles in the issue as well as an overview of the issue’s structure, divided into three parts:Next, we introduce the articles in each of these three parts.Five of the articles in the special issue establish and explore critical foundations of learning with social media in an algorithmic age. In the article, “Refreshing the affinity space concept: Evolving understandings of learning via social media platforms in an algorithmic age,” Oliveri and Carpenter offer a new look at affinity spaces, taking into account sociocultural perspectives. Affinity spaces are a concept first introduced by Gee (2004) and have become a common framework for social media research across various platforms, including Facebook (Field, 2015), Instagram (Carpenter et al., 2020), X/Twitter (Carpenter et al., 2022; Greenhalgh et al., 2020; Rosenberg et al., 2016), Reddit (Carpenter and Staudt Willet, 2021; Czauderna et al., 2024; Na and Staudt Willet, 2022; Na et al., 2024) and TikTok (Carpenter et al., 2024). The conceptual piece by Oliveri and Carpenter in this special issue gives an overview of this body of work that incorporates affinity spaces and argues for an updated theory to match the new ways social media platforms and algorithms mediate social interactions and experiences. The goal of this article is to foreground three new perspectives when considering affinity spaces on social media platforms: Whether or not future social media studies frame their work in terms of affinity spaces, the questions raised by Oliveri and Carpenter offer critical, foundational principles worth considering in any work in this area.In the article, “‘See results anyway’: Auditing social media as educational technology,” Heath et al. (2024) draw from the theories of discriminatory design (Benjamin, 2019) and technoskepticism (Krutka et al., 2020) to critically examine the potential social harms embedded in the social media platforms of X/Twitter and Instagram. The authors report findings from educational technology audits (Krutka et al., 2019) to argue whether it is ethical and just to use these two social media platforms in educational spaces. Specifically, Heath et al. (2024) use three questions to guide the audit for technoskeptical and discriminatory design understanding: Findings from this audit justify calls for more critical approaches to and focus on the perils of social media use in education − a necessary balance to the largely positive treatment of the possibilities of social media for the past decade of scholarship. The article concludes with a call to move beyond merely teaching with social media toward teaching about social media as a means to “develop community, criticality, and more just futures.”In the article, “Children’s sensemaking of algorithms and data flows across YouTube and social media,” Starks and Reich offer empirical evidence to support theories and critiques of digital and algorithmic literacy. The article reports a qualitative focus-group study with 34 US children aged 8–11. The study begins by considering these children’s use of social media platforms YouTube and TikTok, but quickly moves beyond simplistic reporting to explore what children understand about how content is presented to them, what happens to their data and how this moves across platforms, and the strategies children use in response to their own algorithmic experience. Starks and Reich’s findings show that children do not fully grasp the tradeoffs they make in terms of their privacy to gain digital access − necessitating future policies and educational interventions that can regulate platforms and empower users.In the article, “Twisted knowledge construction on X/Twitter: An analysis of constructivist sense-making on social media leading to political radicalization,” Russo et al.(2024) report findings from a content analysis of 16 tweets (and 3,081 replies to those tweets) from a conspiratorial X/Twitter account associated with former Brazilian president Jair Bolsonaro in the weeks preceding the failed coup attempt in January 2023. The authors suggest that these data demonstrate an efficient but “twisted” form of constructivism − that is, learning that is effective in terms of knowledge gathering but unhelpful due to inaccuracies. Through qualitative coding, Russo et al.(2024) identified five characteristics of social media platforms that support a learning environment that is conducive to spreading political misinformation: The authors argue that future work should investigate the role of facilitation to support healthy constructivist learning.In the article, “What sources do individuals use to validate arguments in scientific discourses today? An exploratory study of YouTube comments on vaccination,” Kang et al.(2024) report findings from a content analysis of 584 randomly sampled comments to eight YouTube videos pertaining to vaccine information. Findings show that the majority of comments using URL links to support their arguments were from anti-vaxxers directing readers to vaccine misinformation. Many of these links led to other videos on YouTube that had been “removed for violating community guidelines” or marked as “video unavailable;” other links led to research papers, but usually these only cited with direct quotes or the title of the paper in isolation − often misrepresenting the purpose and context of the research. Kang et al. interpreted these findings to note both the benefits and detriments of YouTube. On the positive side, discourse in YouTube comments allows individuals to heighten information processing skills by sharing knowledge and constructing knowledge in an informal learning environment. However, on the negative side, this discourse also demonstrates how individuals can purposefully misrepresent scientific research to further a personal agenda with an audience unprepared to critically interpret the meaning on their own. The authors concluded that increased digital literacy is required by social media users to become aware of the types of information and sources being presented.Collectively, these first five articles establish a critical foundation for an updated understanding of social media today − notably, that social media research needs to move beyond positive reports of possibilities with social media toward critical reflection and consideration of potential perils of social media. These five studies direct attention toward deeper consideration of sociocultural context and the effects of platformization and algorithms in future work on social media in education.Two of the articles in the special issue address teachers’ self-directed use of social media for learning. In the article, “Exploring the use of social networks for professional development by Spanish teachers,” Marcelo-Martínez et al. (2024) used a survey and interviews to compare social media use by pre-service, beginning and experienced teachers in Spain. The authors found differences in how early career and experienced teachers used social media platforms. Pre-service and beginning teachers tended to access materials and resources, consuming content and playing more observational roles. In contrast, experienced teachers were more often characterized by active forms of engagement and contribution, including the production of content. This study broadens understanding of teacher social media use by offering findings from the context of Spain; prior research on social media use in education has overwhelmingly come from the USA, and other primarily English-speaking contexts such as the UK, Australia and Canada (Barrot, 2021). The authors highlight that there is not a single story of teacher social media use, as platforms may be used in quite distinct ways by individuals within the teaching profession. These distinct uses may in some cases be linked to different needs associated with different stages in teachers’ professional journeys.Following up on the topic of early career teachers’ social media use is the article, “Understanding beginning teachers’ socio-ecological challenges: Self-directed learning in the r/Teachers subreddit” by Na and Staudt Willet. The authors explored posts relevant to challenges experienced by new teachers. While Marcelo et al. contribute breadth by addressing various social media platforms in their study, Na and Staudt Willet go in depth regarding teachers’ use of a single space, r/Teachers, with a single platform, Reddit. The authors paid particular attention to the norm of anonymity that characterizes Reddit. They found that posts reflected diverse and complex challenges, and that new teachers appeared to use r/Teachers in an effort to overcome these challenges as self-directed professional learners. Na and Staudt Willet identified various challenges for teachers who were marginalized in different ways and considered how an anonymous space such as r/Teachers may prove attractive for the discussion of some challenges these teachers experience. This article highlights how different social platforms feature different technological designs and algorithms, accompanied by distinct affordances and constraints for users.Five of the articles in the special issue address young people’s formal and informal learning with social media. Importantly, all five papers highlight a key concern for this Special Issue: the potential and pitfalls of leveraging social media for academic and/or social supports at varying levels of education. For instance, Barany et al., 2024 in “Learning designs that empower: Navigating sandbox data science at the intersection of computing, big data, and social media” present an illustrative youth case study that suggests the pedagogical benefits and challenges of using “scraped” data from X/Twitter to teach data science to US high school students in a formal learning environment. The authors identify three affordances for data science learning that emerged from the illustrative case: Their work showcases how “big data” drawn from social media can support learning designs and outcomes. The authors’ unique “sandbox” approach − an original pedagogical framework to support open-inquiry − will be of interest to educators who seek to build on learners’ interests and authentic practices to enact culturally relevant pedagogy in support of diverse participation pipelines in science and computer science.Like Barany et al. (2024) Ralph Vacca’s “Algorithmic counterspaces: Exploring Afro-Latino youth information practices using TikTok” addresses social media use among American high-school age youth, but within an informal learning context. Working with an under-researched participant group, this qualitative study explores how Afro-Latino youth engage with mental health content on TikTok. The study reveals that Afro-Latino youth construct temporary and dynamic information spaces that connect to issues of ethnic and racial identity affirmation. Importantly, the work spotlights the challenges posed by these spaces’ temporary and algorithm-dependent nature in maintaining consistent engagement with mental health information. This research offers novel insights into the digital information practices of Afro-Latino youth. It also sheds new light on how racial and ethnic identity dimensions shape information behaviors, highlighting the importance of intersectional identities.Whereas Barany et al. (2024) and Vacca focus on social media use among high school-age adolescents in formal or informal learning contexts, three papers address informal learning with social media among students in higher education. Using a cross-sectional survey design, Dennen et al.’s (2024) “Navigating the high school to university transition with social media: Intensity of use, sense of belonging, and meaningful change” investigates the perceptions and utilization of social media among university students before and during their transition from high school to higher education. The researchers found that participants experienced meaningful change in their social media use from high school to university, which was often attributed to personal growth. Social media intensity correlated weakly but positively with usefulness and sense of belonging. These results point to the need for universities to adapt social media strategies by prioritizing social content, using student ambassadors and customizing feeds. The researchers argue convincingly that universities should support students both online and offline, recognizing learners’ diverse pathways to developing a sense of belonging at the university.Akhmedova et al. (2024) are also interested in university students’ utilization and perceptions of social media for support in an informal learning context. Their first-of-its-kind study, “Social media use among neurodivergent college students: Benefits, harms and implications for education” explores the nature of social media use and related psychological well-being among another under-explored participant group: neurodivergent college undergraduates. Social media have been associated with social benefits and enhanced psychological well-being among non-disabled individuals; it may have similar benefits for neurodivergent young adults with autism, anxiety, attention-deficit and hyperactivity disorder (ADHD) who experience communication differences. This paper reports descriptive statistics from survey results to contextualize qualitative analysis of students’ social media use (e.g. purposes, practices, benefits and used Instagram, TikTok and YouTube to well-being primarily through positive relationships and positive benefits of using social media to their identity and few These novel insights will be of interest to teachers, and other who to support young adults in leveraging their and to address digital (2024) in article, “Navigating academic and life challenges in the The role of social media for employs a qualitative research design to data and social media from another under-explored participant group: students in US of students’ social media use positive role in students address and social challenges of American higher education as well as some of the (e.g. digital This work highlights the need for future studies of students in different and contexts, across different of higher education and research this double special issue a set of that are novel in a of ways (e.g. in the of participants or context for the research or in the implications These articles contribute to the on social media in education by advancing as We the authors for their high and the for the authors in the of their
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it