Curriculum structure, not just course content or instruction, shapes how quickly and equitably students reach graduation. This session introduces Curricular Analytics, a research-based framework that models degree programs as networks of courses and prerequisites to surface hidden structural barriers: long prerequisite chains, bottleneck "gatekeeper" courses, and dead-end requirements that can add semesters to a student's path without adding rigor.
We'll walk through the core metrics (delay factor, blocking factor, structural complexity), share complexity data from Texas State programs, and show how peer institutions, Colorado State, UT San Antonio, and the University of South Florida, have used this data to reduce structural complexity while maintaining academic standards.
No prior knowledge of Curricular Analytics is required. Open to all faculty.