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LAK23 Workshop:

Analytics Revealing Systemic Inequities At Different Scales

Analytics applied to the student record, although limited for describing individual student learning and experiences, are effective in revealing institutional systemic inequities at different levels and in different spaces.

In this face-to-face session, we will discuss and share analytical tools developed by students, faculty, and staff engaged in the Measurement Working Group of the Sloan Equity and Inclusion in STEM Introductory Courses (SEISMIC) Collaboration. We have been engaged in establishing metrics for measuring equity and inclusion in foundational STEM courses, conducting the measurements, and identifying actionable data to promote change.

In the course of this path of discovery, the group established theoretically informed guidelines for framing, analyzing, and interpreting quantitative data in support of equity goals in STEM. Building on this understanding, we have focused analyses on institutional structural inequities at different scales, revealing inequities in the students’ experience in their first STEM course, at the curriculum level, and at the course level.

The goal of this Mini-Symposium and Tutorial is to provide participants with these theoretical and practical tools first by presenting the methods and results of the studies and then by providing hands-on training, ultimately empowering participants to apply these analyses to their own institutions’ data.

Contact Stefano Fiorini (sfiorini@indiana.edu) and Becky Matz (rlmatz@umich.edu) with questions. 

Schedule

Mini-Symposium

Integrating critical approaches into quantitative STEM equity work
Meaghan Pearson, PhD Candidate, Combined Program in Education and Psychology, University of Michigan

Exposing inequity: A multi-institutional analysis of systematic advantages in introductory STEM courses
Sarah Castle, PhD Candidate, Program for Mathematics Education, Michigan State University

Cross-institutional comparison of curricular pathways to reveal minoritizing structures
Stefano Fiorini, Manager, UITS Research & Analytics, Indiana University

Exploring the role of class and college composition on student performance in first-STEM classes
Angel Sylvester, PhD Candidate, AI/Robotics College of Science and Engineering, University of Minnesota

A multi-institutional analysis of opportunity gaps amongst biology students across STEM courses revealing differential outcomes for undergraduate students across disciplines
Kameryn Denaro, Research Specialist, Postsecondary Education Research and Implementation Institute (PERI2), UC Irvine

Do equity gaps associated with identities that confer systemic advantages persist into upper-division biology?
Victoria Farrar, Postdoctoral researcher, Department of Neurobiology, Physiology, and Behavior, UC Davis

 

Tutorial

The Tutorial will provide participants with an overview of the data structures used for these analyses as well as a synthetic dataset for the application of the analytical methodologies presented during the Mini-Symposium. 

 

Organizers, Facilitators, and Speakers

 

Sarah Castle

gadysara@msu.edu

 

Kameryn Denaro

kdenaro@uci.edu

 

Victoria Farrar

vsfarrar@ucdavis.edu

 

Stefano Fiorini

sfiorini@indiana.edu

 

Becky Matz

rlmatz@umich.edu

 

Meaghan Pearson

meaghanp@umich.edu

 

Angel Sylvester

sylve057@umn.edu

 

Nita Tarchinski

nitaked@umich.edu

 

Sophia Tong

xstong@umich.edu