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
from pipelines to pathways in the study of academic progress
This brief essay frames our scientific ambition.
the production of merit
How do young people make sense of their life experiences and explain them to others?
Merit is a complex idea in American culture. This project examines how admissions professionals and college hopefuls collaborate to sustain the merit idea in routine acts of soliciting, writing and reading applications.
Leads
- AJ Alvero
- Sonia Giebel
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.
course consideration
What matters to students as they consider college classes?
This project investigates how students use the Carta platform to browse and select courses by extracting multi-stage screening rules from student activity.
observing major selection
Given seemingly limitless options, how do students select their majors?
We use novel archival transcript data and computational methods to identify how students navigate elective curriculums and commit to majors.
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.
an applied science to support working learners
Blending the worlds of school and work
Working learners simultaneously pursue paid employment and postsecondary education. They are the majority of Americans in college, yet a full understanding of their assets and needs has been limited by the tendency for educators, employers, and researchers alike to presume that work and school are separate worlds.
This project is part of a national effort to correct this presumption and build tractable knowledge to improve opportunities for working learners.
Lead
- Mitchell Stevens
ambiguous credentials
How do people make sense of learning credentials that are not college degrees?
Badges and alternative credentials of wide variety are proliferating in the global postsecondary ecosystem. This project investigates how learners and employers make sense of novel educational certifications.
Lead
- Mitchell Stevens
universities and the future of work
US research universities are vital engines of scientific knowledge and inter-institutional relationships that can help the nation anticipate — and shape — the future of work
Leads
- Mitchell Stevens
- John Mitchell
fairness and ethics in computational assessment
How can AI inform academic evaluation?
This project leverages a corpus of over 800,000 college applications to determine how education data science might inform norms and practices of fairness and ethics in educational evaluation.
course evaluations and peer review
How do students use course reviews to make choices?
Students rely on advice from their peers in navigating academic coursework and choice points. This project leverages a large cache of student-authored course reviews to understand how students make sense of learning experiences and give help to one another.
learning from MOOCs
What good is massive?
Massively open online courses (MOOCs) generated extraordinary scientific insight. Here are just a few things we are learning.
Leads
- John Mitchell
- Mitchell Stevens
- René Kizilcec
- Andy Saltarelli
pandemic response
How is COVID-19 influencing learning pathways? How might the pandemic shape the future of learning?
The COVID-19 pandemic has brought spectacular new challenges for educators and learners. Digital platforms have become essential tools in meeting that challenge.
Leads
- John Mitchell
- Mitchell Stevens
STEM pathways
How do students' STEM pathways emerge?
This project investigates how students move through science, technology, engineering, and mathematics (STEM) majors and careers.
Leads
- Marissa Thompson
- Phillip Hernandez
- Monique Harrison
- Shima Salehi
Carta platform
What courses should I take next term?
Carta is a web-based tool that supports informed academic decision-making at Stanford University. Carta integrates information from multiple intramural sources to make course comparisons and academic planning easy for students. Designed and built by students to serve students, Carta also scaffolds Pathways Lab research projects.
ITHAKA/Stanford assemblies
What is responsible use?
This project entailed a series of assemblies co-hosted by ITHAKA S+R and Stanford University to develop shared understandings about responsible use of student data in higher education. Outputs of those convenings in 2014 and 2016 have contributed to ongoing international discussion about data-use practice and governance in a wide variety of sectors. Find documentation of the assemblies here.