Tracy Sweet
University of Maryland, MD·Education Research
Big questions in STEM education — whether a curriculum change improves outcomes across hundreds of classrooms, how student networks shape persistence, how learning develops over years — require quantitative methods that many education researchers were never trained to use. The shortage of early career scholars who can design and analyze large-scale studies limits what the field can answer.
- Fields
Education Research
Mathematics & Statistics
Social Science
- Topics
STEM education research
quantitative methods
research design
- Grants
- 1 known grant, through Jun 2029
What they work on
- Train three cohorts of 17 early career STEM education scholars through year-long intensive institutes on research design, measurement and data analysis for large-scale studies in K-12 and postsecondary settings.
- Build scholars' capability in specific quantitative methods, including structural equation modeling, multilevel and longitudinal models, latent class and mixture models, Bayesian methods, social network analysis and machine learning.
- Support each scholar through pairing with a methods mentor and a graduate student facilitator, live-stream workshops and peer collaboration, toward a completed data analysis or full grant proposal during the mentored year.
- Incorporate training on the use of AI in research methods and in disseminating findings into the institute curriculum for STEM education researchers.
More about the research
This project addresses that gap directly by running a structured training institute for early career STEM education researchers working in K-12 or postsecondary settings.
Why it matters
Education policy and practice decisions rest on the quality of the studies behind them. By training more than 50 early career scholars to design well-measured, well-analyzed large-scale studies, the project could raise the standard of evidence available to teachers, administrators and funders making decisions about STEM instruction in K-12 schools and colleges.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Brendan Eagan
University of Wisconsin-Madison, WI·Education Research
Train three cohorts of 30 mostly underrepresented early-career researchers in quantitative ethnography (QE) through the Accelerator, Incubator, Booster and Multiplier workshop sequence covering methods, feedback, writing and teaching.
Azadeh Bolhari
University of Colorado Boulder, CO·Education Research
Train about 48 STEM faculty and postdocs to approach education research as a design problem, using the ProQual Institute's 4-step program in interpretive research design.
Hok Chio Lai
University of Southern California, CA·Psychology·Early-career
Develop a robust optimization algorithm for data harmonization that puts different instruments measuring the same concept on a common scale while also correcting for measurement bias across groups.
The school
University of Maryland: 49 labs on PI Pages, $1.5B a year on research, 602 research doctorates a year.
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