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Creators/Authors contains: "Sexton, Stacey"

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  1. Broadening participation in computing (BPC) has been a key focus of the National Science Foundation (NSF) for over two decades. Its aim is to support students and faculty from historically underrepresented groups, including women, people with disabilities, and certain racial and ethnic groups. Within these communities, the diverse range of gender and sexual identities remains overlooked in computing education research (CER). To address this invisibility, this panel will discuss the benefits of integrating LGBTQIA+ perspectives. The moderator will provide context, define relevant terms, and set ground rules for discussion. The panelists will offer insights from a variety of perspectives, including: a discussion of the policy landscape impacting LGBTQIA+ students and the importance of incorporating their perspectives as researchers and participants; the erasure of queer history in computer science and advocate for LGBTQIA+ inclusion, considering the humanitarian calling for the field and CS educators in our tech-driven world; the current resistance to supporting LGBTQIA+ scholarship in computing, advocating for an inclusive approach; and finally, the experiences of marginalized individuals in CS education and ways to support them, emphasizing inclusivity through storytelling and personal narratives. The panel aims to increase visibility, understanding, and collaboration between the computing education research community and LGBTQIA+ individuals. By acknowledging and integrating diverse perspectives, we can begin to create a more inclusive, equitable computing landscape. 
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  2. While many efforts have begun to increase the diversity of learners in computing and engineering fields, more inclusive approaches are needed to support learners with intersectional identities across gender, race, ethnicity, and ability. A group of 15 experts across a range of computing, engineering, and data-based disciplines joined experts from education and the social sciences to build a plan for intersectional policy, practices, and research in broadening participation in computing and engineering (BPC/BPE) efforts that is inclusive of gender identity. This paper presents findings from the workshop including near and long term agenda items for intersectional research about the inclusion of gender identity in the computing and engineering education research communities; recommendations for advancing collective understanding of and ability to implement principles of intersectionality in future work and; and highlights from existing work, researchers, and thought leaders on the inclusion of gender identity in BPC/BPE initiatives that inform this research agenda. In this report we’ll discuss the origin of the workshop idea, the experience of pulling together the workshop and lessons learned around implementing it, and finally we’ll report about the outputs and emerging outcomes of the workshop experience. This workshop report will contribute to fostering a space where gender expansive work is valued and valuable for those doing, receiving, and being represented by this work. It will also offer readers the opportunity to conceptualize how to expand and refine the inclusion of gender identity as part of their current and future BPC/BPE initiatives. We end with an explicit call for more gender expansive and gender liberationist work be undertaken through the auspices of ASEE. 
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  3. Lack of diversity and high dropout rates among underrepresented students plague the CS discipline. We developed, administered, and validated survey scales measuring social factors that impact the retention and graduation of under-represented CS undergrads at two institutions. Results revealed significant differences between students who identify as men vs. women in terms of computing identity and confidence, and between black and non-black students in terms of familiarity with future opportunities. 
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    In 2017 a project was started to form a connected community of practice (CCOP) of projects funded to conduct computer science education research through a research practice partnership methodology. In this poster, organizers from that CCOP detail strategies to encourage ongoing exchange and collaboration in the community of researchers. Strategies began with offering resources broadly useful to all projects in an early phase of their RPP work. Over time, through surveying participants, a more theme-based strategy to appeal to subsets of the community was employed. The poster explores the themes used in the third year of the project and share attendance and engagement data. Generalizable recommendations for encouraging shared data gathering goals and resource curation are offered for similar communities of practice devoted to researching computer science education, and ideas on how organizers can measure the success of such communities are shared. 
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  6. Teacher professional development (PD) is a key factor in enabling teachers to develop mindsets and skills that positively impact students. It is also a key step in building capacity for computer science (CS) education in K-12 schools. Successful CS PD meets primary learning goals and enable teachers to grow their self-efficacy, asset and equity mindset, and interest in teaching CS. As part of a larger study, we conducted a secondary analysis of CS PD evaluation instruments (). We found that instruments across providers were highly dissimilar with limited data collected for measures related to teacher learning, which has implications for future K-12 CS education. Likewise, the instruments were limited in being connected to student learning and academic growth. As a way to enable PD providers to construct measures that align with known impacting factors, we offer recommendations for collecting demographic data and measuring program satisfaction, content knowledge, pedagogical content knowledge, growth and equity mindset, and self-efficacy. We also highlight questions for PD providers to consider when constructing their evaluation, including reflecting community values, the goals of the PD, and how the data collected will be used to continually improve CS programs. 
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