Gaining Insights into Group-Level Course Difficulty via Differential Course Functioning
Frederik Baucks, Robin Schmucker, Conrad Borchers, Zachary A. Pardos, and Laurenz Wiskott

TL;DR
This paper introduces Differential Course Functioning (DCF), an IRT-based method to detect and analyze disparities in course difficulty across student groups, controlling for overall student performance levels.
Contribution
The study presents DCF as a novel methodology for curriculum analytics that isolates course-specific difficulty differences among diverse student populations.
Findings
DCF detects inequities in course difficulty across student groups.
Transfer students show minor variations in course difficulty, indicating effective course design.
Major co-enrollment analysis links DCF effects to course content alignment with student backgrounds.
Abstract
Curriculum Analytics (CA) studies curriculum structure and student data to ensure the quality of educational programs. One desirable property of courses within curricula is that they are not unexpectedly more difficult for students of different backgrounds. While prior work points to likely variations in course difficulty across student groups, robust methodologies for capturing such variations are scarce, and existing approaches do not adequately decouple course-specific difficulty from students' general performance levels. The present study introduces Differential Course Functioning (DCF) as an Item Response Theory (IRT)-based CA methodology. DCF controls for student performance levels and examines whether significant differences exist in how distinct student groups succeed in a given course. Leveraging data from over 20,000 students at a large public university, we demonstrate DCF's…
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