NSF Methods Training Institute for STEM Education Research

Project Team at the University of Chicago
Guanglei Hong (PI)
Yanyan Sheng (Co-PI, Executive Director)
Stephen Raudenbush (Co-PI)
Darnell Leatherwood (Project Coordinator)

Project Team at Michigan State University
Ken Frank (PI)
Kaitlin Torphy (Co-PI)
Jiliang Tang (Co-PI)

Goshen Education Consulting, Inc.
Matt Feldmann (Evaluator)



Housed at the University of Chicago, and a joint effort with Michigan State University, the summer institute in advanced research methods for Science, Technology, Engineering, and Mathematics education research (SIARM for STEM) is funded via a 3-year grant from the National Science Foundation (2020-2023).

The project team include leading experts of different disciplines who have developed cutting-edge quantitative and computational methods and directly contributed to STEM education research. The 11-member advisory board consists of a diverse group of leading scholars and leaders of minority-serving institutions and funding agencies who have made major contributions to research and practice concerning educational equity and institutional diversity.

The team will select a diverse cohort of 22 NSF Fellows of STEM Education Research among early- and mid-career scholars, especially those under-represented in STEM, with the goals of:

  • (a) helping Fellows master rigorous and novel applications of advanced methods to STEM education research,
  • (b) providing continuous methodological support in research planning, data analysis, and publication,
  • (c) creating a community that prepares Fellows to take leadership in advancing STEM education research and effectively serving as role models for the next generation of a diverse population of students.

This training will focus on methodological challenges that arise in studies that aim to improve STEM education, with a particular focus on understanding the sources of unequal access to STEM learning opportunities and evaluating strategies for transforming STEM education to advance equity and inclusion. In pursuing these questions, the greatest methodological challenges include research designs and causal inference, measurement, social network analysis, multilevel modeling, causal mediation analysis, and computational methods for analyzing qualitative and social media data.

Is This a Great Opportunity for You?

– Are you studying STEM education in your research?

– Are you interested in issues of education equity?

– Do you want to explore the possibility of applying new quantitative or computational techniques in your work?

– Are you excited about joining a community of current and future leaders in STEM education research?

Scroll to Top