We present the Center for Inclusive Computing's data collection and visualization system, which enables computing departments to track and visualize their enrollment and course outcome data intersectionally and longitudinally. The system tracks the impact of institutional changes in how computing (particularly the introductory sequence) is discovered and experienced by undergraduates as measured by course outcome and persistence data. To date we have worked with and collected data from 52 U.S. computing departments. Collected data spans 2018-present and contains term-by- term, intersectional course enrollment and outcome data for CS 1-3, while also tracking declared majors and persistence to graduation. Drawing on our experience working with these universities we present guidelines for the analysis of intersectional, longitudinal data alongside our recommendations for actionable next steps. We present three case studies grounded in an analysis of CS1, demon- strating how an institution can understand their own computing program and develop interventions-specifically with an eye toward broadening participation in computing.

We present an adaptable curriculum for training undergraduate and graduate teaching assistants (TAs) in computing disciplines that is modular, synchronous, and explicitly mirrors the teaching techniques that are used in our classes. Our curriculum is modular, with each component able to be expanded or compressed based on institutional needs and resources. It is appropriate for TAs from CS1 through advanced computing classes. In addition to being easily adjustable to institutional needs, this curriculum holds two important positions. First, that synchronous training is most effective. Second, that it is vital the curriculum is designed based on peer-to-peer learning and actively incorporates abstract pedagogical reflection into the materials. When TAs are taught the content, it is grounded in the same techniques that we are encouraging them to use and that, as computing faculty, we ourselves use. Finally, we posit that student-TA interactions are a specific site of amplifying and attenuating inequality in computing classrooms. By providing a curriculum that is easily accessible and sensitive to both the technical and interpersonal needs of pedagogical training, we aim to create a more welcoming environment for all learners in computing disciplines. Based on our experience teaching this curriculum to more than 900 TAs at two institutions in four different formats, we offer insights and recommendations to using and adjusting this curriculum under varying circumstances. We release the curriculum in its entirety to the computing education community (at https://cic.northeastern.edu/ta-training/).

We implemented a model for grading weekly assignments in an intermediate data science course that explicitly gave students useful feedback on their code while not evaluating it on the traditional metrics of correctness or style. This ungrading policy was used in a 150-student course led by 2 instructors and 11 Teaching Assistants (TAs). Our ungrading policy was designed to extend empathy towards students and to give them useful, actionable feedback. Our policy reduced the stress that students felt each week, stabilized the amount of time they spent on assignments, and ask them to reflect on their code to request feedback from the teaching team. Students could receive full credit for a homework assignment even if it was incomplete, making office hours less hectic. Students could also submit their homework after working on it for a certain number of hours, even if a bug still existed. Our ungrading policy also helped our TAs feel valued. They gave feedback based on general expectations rather than a point-based rubric, allowing them to share their own expertise. TAs gave feedback only when requested, which was therefore more likely to be read.

Increasing attention to the role of ethical consideration in computing has led to calls for greater integration of this critical topic into technical classes rather than siloed in standalone computing ethics classes. The motivation for such integration is not only to support in-situ learning, but also to emphasize to students that ethical consideration is inherently part of the technical practice of computing. We propose that the logical place to begin emphasizing ethics is on day one of computing education: in introductory programming classes. This paper presents one approach to ethics integration into such classes: assignments that teach basic programming concepts (e.g., conditionals or iteration) but are contextualized with real-world ethical dilemmas or concepts. We report on experiences with this approach in multiple introductory programming courses, including details about select assignments, insights from instructors and teaching assistants, and results from surveys of a subset of students who took these courses. Based on these experiences we provide preliminary plans for future work, along with a roadmap for instructors to emulate our approach and suggestions for overcoming challenges they might face.