Seminar 2022 Schedule

Monday 19 September
Noon—1.30 pm PDT

Kickoff: Motivation for the seminar and flash introductions

At this inaugural session, Mitchell offers a brief history of the Stanford Pathways Lab and the ambitions of the seminar for the coming year. Attendees should be prepared to offer a 2-3 sentence introduction to themselves and their work (no slides, please).

We also will huddle about setting norms for the seminar.

Session Lead

  • Mitchell Stevens, Stanford

Thursday 6 October
1—2 pm PDT

From pipelines to pathways in the study of academic progress

Much research on undergraduate education speaks of pipelines, but that metaphor is suboptimal for exploiting scaled data and elides the complexity of academic progress. We integrate insights from multiple scientific domains to specify a heuristic of pathways that better fits both the phenomenon and available empirical material.

This paper defines academic pathways as joint outcomes of curricular programs that variably provide course options, and sequences of considered and selected academic opportunities. Pathways can be enabled, inhibited, or prevented by institutions; and taken, avoided, and forged by students. With investments in data infrastructure, a coherent science of academic pathways promises new inquiries and strategies to improve student persistence, timely degree completion, equity and inclusion in higher education.

Session Lead

  • Rene Kizilcec, Cornell

Monday 17 October
Noon—1 pm PDT

Observing undergraduate pathways at close range

Since Summer 2019, our team has been interviewing a panel of approximately 80 undergraduates as they navigate Stanford University. We interview these students three times a year near the drop/add period of each academic term, generating fine-grained data about academic decision-making and identity development. This presentation provides an overview of the scientific ambitions of our study, seeking collegial input on our research priorities for the coming year.

Session Leads

  • Mitchell Stevens, Stanford
  • Monique Harrison, Penn
  • Phil Hernandez, Stanford

Thursday 10 November
1-2 PM PDT

Major requirements, peer composition, grading practices and student course trajectories

UC-Irvine’s undergraduate measurement project has collected unprecedented data on student experiences, trajectories and outcomes. The data include administrative records, learning management system logs, longitudinal surveys, experiential sampling responses and performance assessments. UCI researchers will focus this session on using some of that data to explore how major requirements, peer composition and grading practices are associated with student pathways.

Session Leads

  • Richard Arum, UC-Irvine
  • Xunfei Li, UC-Irvine
  • Oded McDossi, UC-Irvine

Monday 21 November
Noon—1 pm PDT

Forum on grading regimes

The presentation originally scheduled for 21 November has been postponed due to illness. Instead we will continue the rich dialogue begun by the UC-Irvine team on 10 November. As a working definition, let’s say that grading regimes are systems whereby official scores and grades are assigned to academic coursework. Grading regimes include such things as: letter-grade vs. pass/fail grades; curved grading systems; intramural variation in grade distributions; student cultures around the meaning of grades; and minimum grade or GPA requirements as criteria for access to specific programs.

The forum will consist of “flash” presentations (five minutes max) of completed scholarship or work in progress on this broad topic. If you would like to offer a flash presentation, please write to Mitchell at First come, first served.


Session Leads

  • Richard Arum, UC-Irvine
  • Mitchell Stevens, Stanford

Thursday 8 December
1 - 2 PM PDT

Understanding the black box of broad-access institutions

Broad access institutions serve a key role in providing education to non-traditional students. We introduce findings from the first year of a five-year Gates Foundation Grant at Western Governors University that aims to identify and solve equity gaps in access, attainment, and outcomes at institutions in collaboration with external academic researchers. This agenda will focus on how institutions can better operationalize academic transcript data from students’ current and prior institutions to inform course planning and articulation agreements. We also explore how Natural Language Processing can act as augmented intelligence for college counselors and early warning systems. Lastly, we consider how this work can be used to construct a virtuous cycle of qualitative and quantitative work informing one another for institutional improvement.

Session Leads

  • David Lang, Western Governors University
  • Ben Listyg, Western Governors University
  • Kris De Pedro, Western Governors University