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The correct sequence of courses in a curriculum can ensure that students develop their knowledge and skills holistically. The challenge level can also be more evenly distributed. Creating these sequences is difficult because curriculum designers must consider multiple potentially conflicting criteria simultaneously. There currently exists a dearth of tools for analyzing the curriculum that incorporates course dependencies as defined by curriculum designers while also considering students’ pathways through the curriculum. In this paper, we present Curri, a data-driven curriculum visualization system that scrapes dependencies from our university’s published curriculum and leverages student academic data to determine when, on average, students take each course. We evaluate our approach with a case study and two focus groups. This work provides initial evidence that considering both dependencies and students’ temporal performance leads to new analyses and insights. Figure 1: Curri, a curriculum visualization system that leverages curricular dependencies (prerequisites) and student data to show students’ pathways through the curriculum. Each course is represented by a circle, lines represent a dependency, and the placement of courses is based on when students take the course on average.

Curri: A Curriculum Visualization System that Unifies Curricular Dependencies with Temporal Student Data