Collecting, Analyzing, and Acting on Intersectional, Longitudinal Data and Pass/Fail/Withdraw Rates in Computing Courses
Felix Muzny, Megan Giordano, Emma Sommers, Carla E. Brodley · 2024
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.