This lightning talk describes ongoing research that aims to examine the impact of an in-person residency program as part of an online bridge program toward a masters in computer science. Three times throughout the online bridge program, the university arranges travel for all participating students to meet up for 2-3 days of in-person classes and other programming. Participating students did not graduate with undergraduate degrees in computer science, and their previous experience in computer science ranges from minimal to none at all. A goal of the study is to determine if the series of in-person residencies have an impact on the students' sense of belonging, connections with peers and instructors, learning outcomes, and career choices. Preliminary findings indicate promising ways to broaden participation in computing toward non-traditional CS learners. For example, residencies increased students' comfort with reaching out to instructors and peers for help. Students entering the program expressed feeling less alone after meeting their peers in-person and recognizing that they share a lack of experience in computer science with their peers. The research is in the beginning stages of data collection and analysis. SIGCSE participants are encouraged to attend the talk to learn more about the structure and impact of a residency for a bridge program toward a masters in computer science.

This study investigates the experiences of students new to computer science (CS) to uncover both barriers to and opportunities for support in early CS education.Using interviews, we explore students' initial motivations, encountered challenges, and changing views of the field across three separate interviews throughout a semester.Insights from this research aim to guide the development of inclusive, engaging CS curricula that better support diverse learners during their critical early exposure to the discipline.

Collaborative, playful learning represents an important avenue to mastering a range of skills within computer science education. This research presents findings from interviews with 9 members of an online community that started out as a gaming league and transitioned into a game development team. Community members learned programming skills to contribute their ideas to the game and participate in activities based around game development. Drawing on these experiences, we identify key elements from informal learning that can improve computer science education: 1) playful projects can help learners overcome barriers to participating in computer science; 2) community closeness facilitates a collaborative learning environment to support developing expertise in specific computational skills. We consider these findings in the context of learning as an everyday social practice, and discuss means of developing playful learning communities in computer science classrooms.

Data are wielded to shape public opinion, particularly in electoral contexts where the role and veracity of information is questioned. This post-truth era is characterized by world events in which facts too often are obfuscated and evidential standards are abandoned. To study how data are used to influence pressing and divisive contemporary issues, this paper explores the rhetorical work that quantitative data are doing through the blogging practices of advocacy organizations during the highly-polarized month preceding the 2016 United States elections. We present results of a qualitative content analysis of the quantitative data used in 337 blog posts published by five pairs of conservative and liberal advocacy organizations over the course of the month leading up to the 2016 US elections. We identify key data rhetoric practices along partisan lines and contribute an analytic framework-evaluating ethos, pathos, and logos- that can be used to analyze the rhetorical use of data in other contexts. We then characterize two different imaginaries that come into conflict in this research: 1) the political imaginaries being promoted through organizational blogging and 2) the sociotechnical imaginary of the data economy, foregrounding differences in the epistemic value of data in each. We conclude by outlining research challenges and trajectories for future research within each of the two imaginaries of data.

Social media platforms make trade-offs in their design and policy decisions to attract users and stand out from other platforms. These decisions are influenced by a number of considerations, e.g. what kinds of content moderation to deploy or what kinds of resources a platform has access to. Their choices play into broader political tensions; social media platforms are situated within a social context that frames their impact, and they can have politics through their design that enforce power structures and serve existing authorities. We turn to Pillowfort, a small social media platform, to examine these political tensions as a case study. Using a discourse analysis, we examine public discussion posts between staff and users as they negotiate the site's development over a period of two years. Our findings illustrate the tensions in navigating the politics that users bring with them from previous platforms, the difficulty of building a site's unique identity and encouraging commitment, and examples of how design decisions can both foster and break trust with users. Drawing from these findings, we discuss how the success and failure of new social media platforms are impacted by political influences on design and policy decisions.

Broadening participation in computing among underrepresented groups is important for not only increasing the workforce in computer science careers but also for ensuring that a broad range of stakeholders can contribute to technology development. However, stereotypes and stereotype threat represent a major barrier to underrepresented groups engaging with computer science education. To investigate alternative paths into computational work that sidestep the pressures of stereotypes, we interviewed 22 people working on computational projects in transformative fandom, a community centered on media remix and critique. Our participants--primarily women, people of color, and/or LGBTQ+ people--described a set of stereotypes about computing that prevented them from seeing their own highly technical work as computational. However, participants also described projects that not only taught them computing skills but also opened up alternative pathways for involvement in computer science. We draw on these findings to provide recommendations for how educators and professionals might break down stereotypes and incorrect expectations to increase underrepresented groups? involvement and confidence in computer science.

Broadening participation in computing ensures that a diversity of perspectives are involved in creating new technologies. Yet despite initiatives aimed at bringing more diverse groups into computer science as a discipline, underrepresented groups are still under threat to be crowded out of formal computing spaces. However, there are informal spaces where these populations engage in computational projects, learning computing skills outside of traditional academic or industry computing spaces. One such space is transformative fandom. We propose exploring how people in transformative fandom innovate and transform technologies, with an emphasis on their involvement in computational projects by and for marginalized communities.

Within online communities, social norms that both set expectations for and regulate behavior can be vital to the overall welfare of the community--particularly in the context of the privacy and safety of its members. For communities where the cost of regulatory failure can be high, it is important to understand both the conditions under which norms might be effective, and when they might fail. As a case study, we consider transformative fandom, a creative community dedicated to reimagining existing media in often subversive ways. In part due to the marginalized status of many members, there are strong, longstanding norms to protect the community. Through an interview study with 25 fandom participants, we investigate social norms that have been largely effective over time at maintaining member privacy and safety, but also break down under certain circumstances. Catalysts for these breakdowns include tensions between sub-communities and an increasing presence of outsiders, though most prominently, we identify a disconnect between the norms the community needs to support and the design of the platforms they occupy.

When online platforms rise and fall, sometimes communities fade away, and sometimes they pack their bags and relocate to a new home. To explore the causes and effects of online community migration, we examine transformative fandom, a longstanding, technology-agnostic community surrounding the creation, sharing, and discussion of creative works based on existing media. For over three decades, community members have left and joined many different online spaces, from Usenet to Tumblr to platforms of their own design. Through analysis of 28 in-depth interviews and 1,886 survey responses from fandom participants, we traced these migrations, the reasons behind them, and their impact on the community. Our findings highlight catalysts for migration that provide insights into factors that contribute to success and failure of platforms, including issues surrounding policy, design, and community. Further insights into the disruptive consequences of migrations (such as social fragmentation and lost content) suggest ways that platforms might both support commitment and better support migration when it occurs.

Online communities provide support for those who are vulnerable, such as LGBTQ people while coming out. Research shows that social support and personal narrative construction are important when recovering from personal crises and traumatic events. As an online community focused on writing fanfiction and also consisting of a large number of LGBTQ members, transformative fandom provides an opportunity to examine the relationship between support, crisis, and narrative. Through an interview study with 31 LGBTQ fanfiction authors, our findings mirror Herman's model of trauma recovery: these spaces self-organize to support recovery work through constructing "community narratives" that help LGBTQ people establish safety when exploring their identity and build LGBTQ support structures without publicly outing themselves before they are ready, challenge stereotypes, and support others through reshaping existing media that perpetuate inaccurate or harmful LGBTQ narratives. These online communities embody "selective visibility"--that is, though not specifically designed as support structures for identity work and recovery, their design allows people to selectively find and create communities of support for stigmatized issues that they might be unable to safely seek out in other spaces. Based on lessons learned, we generate insights that can inform the design of safe support spaces online.