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Domestic undergraduate computer science students formally learn about machine learning and artificial intelligence in upper-level undergraduate computing programs, yet they must navigate the lure of ChatGPT and other generative Artificial Intelligence tools that have been found to be somewhat accurate at completing early coding assignments. As AI tools proliferate, messaging about their use in academic settings are varied, and access to AI literacy is unknown. Through an investigation of interviews with Pell grant-eligible college students at open-access colleges, we address the following research questions: How do low-income undergraduate interview participants describe their uses of and attitudes regarding generative AI tool use for academic purposes? and What elements of AI digital literacy appear to be accessible to interview participants, based on their descriptive statements? 

This research-to-practice full paper describes a cohort-based undergraduate research program designed to improve STEM retention through structured mentoring and community building. Drawing on the Affinity Research Group (ARG) model, the program fosters faculty-student research collaboration and integrates faculty mentorship training, student-led peer mentoring, and structured interventions, such as research skills workshops and networking events. Each year, faculty from biology, chemistry, computer science, environmental science, and mathematics lead small-group research projects with recruited students who may participate for up to three years. Faculty and students receive ARG training to promote consistent mentoring practices. A credit-bearing, major-specific first-year orientation course supports recruitment and reinforces students’ scientific identity. Faculty also engage in professional development workshops to strengthen student-centered mentoring approaches. Data collection includes surveys, interviews, retention tracking, and weekly journaling to assess STEM identity, belonging, and skill development. External evaluators reviewed the faculty focus groups to assess mentoring effectiveness. Initial findings show strong faculty engagement with the ARG model, with many adopting adaptive mentoring strategies that enhance student support. Students report increased confidence and belonging within their disciplines. However, cross-disciplinary collaboration remains limited, highlighting the need for more intentional networking within the cohort. Students also emphasized the value of peer collaboration alongside faculty mentorship. These results suggest that undergraduate research can serve as a powerful tool for building community and supporting persistence in STEM. Ongoing efforts will focus on expanding networking opportunities, strengthening peer collaboration, and evaluating long-term impacts on student retention. 

In this paper, we describe efforts of an alliance to increase Pell-grant eligible and first-generation student access to active conference participation by systematically including considerations for student basic needs as well as developing professional science skills and knowledge that aligns with industry and graduate school pathways in computer science. We describe how an alliance creates the structure and flexibility for systematic care for student needs and local innovation to improve educational practice regarding conference participation. We describe our lessons learned for improving access to conferences as well as provide recommendations for increasing student access to professional conference benefits. 

In this paper, we describe efforts of an alliance to increase Pell-grant eligible and first-generation student access to active conference participation by systematically including considerations for student basic needs as well as developing professional science skills and knowledge that aligns with industry and graduate school pathways in computer science. We describe how an alliance creates the structure and flexibility for systematic care for student needs and local innovation to improve educational practice regarding conference participation. We describe our lessons learned for improving access to conferences as well as provide recommendations for increasing student access to professional conference benefits. 

In this paper, we describe efforts of an alliance to increase Pell-grant eligible and first-generation student access to active conference participation by systematically including considerations for student basic needs as well as developing professional science skills and knowledge that aligns with industry and graduate school pathways in computer science. We describe how an alliance creates the structure and flexibility for systematic care for student needs and local innovation to improve educational practice regarding conference participation. We describe our lessons learned for improving access to conferences as well as provide recommendations for increasing student access to professional conference benefits. 

In this paper, we describe efforts of an alliance to increase Pell-grant eligible and first-generation student access to active conference participation by systematically including considerations for student basic needs as well as developing professional science skills and knowledge that aligns with industry and graduate school pathways in computer science. We describe how an alliance creates the structure and flexibility for systematic care for student needs and local innovation to improve educational practice regarding conference participation. We describe our lessons learned for improving access to conferences as well as provide recommendations for increasing student access to professional conference benefits. 

This work-in-progress study describes our grant-funded efforts in developing a computer science faculty learning community (FLC) across six California state institutions. With an emphasis on socially responsible computing (SRC), the faculty development effort that prepares faculty for SRC lesson implementation has integrated social scientists with computer science faculty in the rotating leadership team. It works collaboratively to facilitate dialog around experiences of implementing lessons that focus on social justice and ethical decision-making. Our data-driven FLC and course transformation effort was initiated by finding that retention rates in early computing courses at participating institutions were inequitable across demographic groups. The ultimate goal of the Broadening Participation in Computing Alliance for Socially Responsible Computing is to improve the retention rates of LatinX students by increasing their sense of belonging to the field of computer science[1] through deliberate and intentional connections of curriculum to real-world problems and social issues. For this paper, we focused on the faculty experiences of our most recent summer workshop and our reflection on the FLC implementation process. We present our faculty survey data from June 2024 and introduce reflective focus group findings [2], providing conjectures about the effectiveness of our approach. In the discussion, we build recommendations for collaborative professional development of faculty and discuss next steps.