Blogs (4) >>

Not all degree programs are created equal. Indeed, the structure, prerequisites and overall complexity of some programs create barriers that impede student success. Inspired by the methodology of previous papers investigating the inverse relationship between curricular complexity and program quality, in this paper we investigate the relationship between curricular complexity and the representation of women earning CS degrees. We created curricular maps of 60 computer science degrees and calculated measures such as program complexity, course blocking, delay factor, and total math/CS credits to understand complexity’s correlation with the representation of women CS majors. Our results show that degree complexity, blocking factor, and delay factor are all inversely related to the representation of women. In addition, we present the courses that most commonly impede student progress and provide suggestions to enhance degree programs based on the insights gained.

Fri 22 Mar

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10:45 - 12:00
Quantitative Approaches to Understanding BPC EffortsPapers at Meeting Rooms B113-114
Chair(s): Paul Tymann Rochester Institute of Technology
10:45
25m
Talk
Evaluating Identity and Belonging in Computer Science Students: Instrument Adaptation and AnalysisGlobalMSI
Papers
Stephanie Werner University of Illinois, Illinois Workforce and Education Research Collaborative (IWERC), Ying Chen University of Illinois, Illinois Workforce and Education Research Collaborative (IWERC)
DOI
11:10
25m
Talk
A Quantitative Methodological Review of Research on Broadening Participation in Computing, 2005-2022MSI
Papers
Linda Sax UCLA, Chantra Nhien Momentum, UCLA School of Education and Information Studies, Kaitlyn N. Stormes Momentum, UCLA School of Education and Information Studies
DOI
11:35
25m
Talk
Does Curricular Complexity in Computer Science Influence the Representation of Women CS Graduates?CER Best PaperGlobal
Papers
Albert Lionelle Khoury College of Computer Sciences, Northeastern University, McKenna Quam Northeastern University, Carla Brodley Northeastern University, Center for Inclusive Computing, Catherine Gill Northeastern University
DOI