Theoretical classes are widely considered among the most challenging in the undergraduate computer science curriculum; that difficulty impacts different populations of students in different ways. I will describe ongoing efforts to understand and address discrepancies in the required junior-level theory course at Illinois. Analysis of grade data reveals a statistically significant performance difference between men and women in that course, which is not explained by differences in overall GPA or in related course grades.
Jeff Erickson,
University of Illinois Urbana-Champaign
However, an analysis of student survey data reveals other factors that have some explanatory power; controlling for expectations of success, levels of text anxiety, or physiological states such as mood, stress, and fatigue reduced the predictive effect of gender on course grade to statistical insignificance.
Jeff Erickson is the Sohaib and Sara Abbasi Professor in the Siebel School of Computing and Data Science at the University of Illinois Urbana-Champaign. He has published more than 100 papers in computational geometry, computational topology, and other related research areas, as well as a popular free Algorithms textbook and other related educational resources. His more recent research focuses on computer science education, specifically on best practices for teaching algorithm design effectively, equitably, and at scale.