Finding patterns in sequences is central to pathways science. We start from the premise that progress at school and work is cumulative: prior accomplishments set conditions for subsequent ones, with meaningful advancement happening through a series of iterative steps. Pathways researchers use records of sequences to observe variation in progress across thousands of cases; this enables us to offer meaningful advice and coaching to others navigating the same terrain. We also use sequences of prior learners and workers to forecast how subsequent sequences are likely to unfold.

How US undergraduates navigate elective curriculums is an orienting problem for pathways science. The complexity and iterative character of elective choice make it a formidable modeling challenge — and all the more important to tackle since timely progress to graduation is an important goal for students and schools alike. Much of this work has been pursued in the service of building practical tools to assist students in navigating academic options to make better-informed decisions. Learn more about some of these navigation tools below.

Pathways researchers also recognize that computational tools and conceptual heuristics we build to study elective choice will be applicable in other domains, including job search and career trajectories in labor markets.

projects

navigating college

Several research teams in the Pathways Network maintain sophisticated platforms designed to better inform students as they navigate curricular offerings. Check them out!

AskOski — UC-Berkeley; contact affiliate Zach Pardos

Atlas — University of Michigan; contact affiliate Gus Evrard

Pathways — Cornell University; contact affiliate Rene Kizilcec

sequences, forecasts, and navigation

undergraduate cohort study

How do students’ aspirations and choices evolve over the course of their undergraduate careers?

We are following eighty students pursuing their undergraduate careers at a private research university with a comprehensive curriculum. We interview participants each term to learn about their academic predilections and choices. The goal is to understand how students’ identities and adult aspirations co-evolve with their academic experiences.

sequences, forecasts, and navigation
identity, motivation, and emotion

Via sequence visualization tool

Which courses, and why?

The processes through which course selections accumulate into college pathways in US higher education is poorly instrumented for observation at scale. We offer an analytic toolkit, called Via, which transforms commonly available enrollment data into formal graphs that are amenable to interactive visualizations and computational exploration. We explain the procedures required to project enrollment records onto graphs, and then demonstrate the toolkit utilizing eighteen years of enrollment data at a large private research university. Findings complement prior research on academic search and offer powerful new means for making pathway navigation more efficient. More.

sequences, forecasts, and navigation

publications

From pipelines to pathways in the study of academic progress

Enabling the study education and learning as sequential phenomena

Science, 2023

Rene F. Kizilcec, Rachel B. Baker, Elizabeth Bruch, Kalena E. Cortes, Laura T. Hamilton, Zachary A. Pardos, Marissa E. Thompson, and Mitchell L. Stevens

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Forecasting undergraduate majors: A natural language approach

Predicting college pathways based on early coursework

AERA Open, 2022

David Lang, Alex Wang, Nathan Dalal, Andreas Paepcke and Mitchell L. Stevens

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Studying undergraduate course consideration at scale

What role does course consideration play in college students' pathways?

AERA Open, 2021

Sorathan Chaturapruek, Tobias Dalberg, Rene F. Kizilcec, Marissa E. Thompson, Sonia Giebel, Monique Harrison, Ramesh Johari, and Mitchell L. Stevens

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Using latent variable models to observe academic pathways

How are student enrollment decisions best modeled with large-scale datasets?

Proceedings of the 12th Annual Conference of Educational Data Mining (EDM), 2019

Nate Gruver, Ali Malik, Brahm Capoor, Chris Piech, Mitchell L. Stevens, and Andreas Paepcke

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Choices, identities, paths: Understanding college students’ academic decisions

How do students choose their courses?

Annual Meeting of the American Sociological Association (ASA), 2018

Mitchell L. Stevens, Monique H. Harrison, Marissa E. Thompson, Arik Lifschitz, and Sorathan Chaturapruek

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