LAUSR

Description Students and administrators can benefit from new analytics Universities are engines for human capital development, producing the next generation of scientists, artists, political leaders, and informed citizens (1). Yet the scientific study of higher education has not yet matured to adequately model the complexity of this task. How universities structure their curriculums, and how students make progress through them, differ across fields of study, educational institutions, and nation-states. To this day, a “pipeline” metaphor shapes analyses and discourse of academic progress, especially in science, technology, engineering, and mathematics (STEM) (2), even though it is an inaccurate representation. We call for replacing it with a “pathways” metaphor that can describe a wider variety of institutional structures while also accounting for student agency in academic choices. A pathways model, combined with advances in data and analytics, can advance efforts to improve organizational efficiency, student persistence, and time to graduation, and help inform students considering fields of study before committing.