Paths of inquiry

Pathways Lab leverages scientific rigor and peer review to inform improvement of learning opportunities across the life course.

paths to work

The relationship between schools and workplaces is complex and changing rapidly. Our work informs public discourse on how best to scaffold education and learning opportunities over the entire life course.

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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.

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Lead

  • Mitchell Stevens

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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

student narratives

Utilizing a cache of hundreds of thousands of essays submitted with applications to a large public university system, the student narratives team is exploring how young people make sense of their life experiences and represent their accomplishments to others.

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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.

Lead

  • AJ Alvero

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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

sequences and forecasts

Using computational, qualitative and archival techniques to understand how learning paths unfold.

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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.

Leads

  • Monique Harrison
  • Phillip Hernandez

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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.

Leads

  • Marissa Thompson
  • Tobias Dalberg

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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.

Lead

  • Tobias Dalberg

platforms and toolkits

Powerful, user-friendly tools to aid in course search and path discovery.

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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.

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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.

Lead

  • Andreas Paepcke

online learning

What works, what doesn't, and what the future of online learning might be.

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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

  • David Lang
  • John Mitchell
  • Mitchell Stevens
  • Andreas Paepcke
  • René Kizilcec
  • Andy Saltarelli

responsible use

The ubiquity, detail and fidelity of data describing learning interactions brings extraordinary opportunity to improve education -- but also obliges educators to share and deploy data responsibly. Pathways Lab takes these responsibilities seriously and continuously.