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Statistical and Research Methodology in Education

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Contact:

Dr. Charles Laurin
(202) 987-0919
Charles.Laurin@ed.gov

Description:

REQUEST FOR APPLICATIONS:
PDF File FY 2025 84.305D (PDF: 506 KB)
MS Word FY 2025 84.305D (DOC: 229 KB)

The goal of the Statistical and Research Methodology in Education (Stats/Methods) grant program (ALN 84.305D) is to provide a wide range of methodological and statistical tools that will better enable applied education scientists to conduct rigorous education research. Through this grant program, IES invites applications to develop new methodological approaches, to extend and improve existing methods, and to create other tools that can enhance the ability of researchers to conduct high quality, scientific education research.

Currently, Stats/Methods grants are divided into Core (previously Regular) grants and Toolkits grants. Core grants last a maximum of 3 years, with a maximum award amount of $900,000 to support the development of new and improved statistical and research methods and their dissemination to education researchers. Toolkit grants last a maximum of 2 years, with a maximum award amount $350,000 to support the compilation of existing research and information for a given method into toolkits, guidelines, compendia, and review papers that help education researchers understand and apply the method.

HISTORY/BACKGROUND

IES originally supported research on statistical and research methodology through the Unsolicited Grant Opportunities and funded 11 projects before the decision was made to establish a separate Stats/Methods grant program.

In 2009, IES established the Stats/Methods grant program which included the Regular (now Core) grants which support the development of new and improved statistical and research methods and their dissemination to education researchers.

In 2014, Early Career grants were introduced to give early career methodologists an opportunity to apply for a smaller grant in a context that was set off from the applications submitted by well-established methodologists. In FY 2024, the Early Career grants were moved to the Research Training Programs in the Education Sciences grant program (ALN 84.305B) as part of the new Early Career Development and Mentoring Program for Education Research topic so that early career researchers would receive support for both research and professional development. Fourteen Early Career grants had been awarded before the move.

In 2022, Toolkits, Guidelines, Compendia, and  Review Papers (Toolkits) grants were added to support the compilation of existing research and information for a given method into products that help education researchers understand and apply a specific method. One Toolkit grant has been award.

By 2023, IES had made 115 Stats/Methods grants: 14 under Unsolicited, 86 Regular or Core grants, 14 Early Career grants, and 1 Toolkits grant for a total of over $77 million in funding.

Why is Stats/Methods Unique? Many grant competitions held by IES are intended to support research that directly affects students and/or teachers in the classroom. The field, however, also needs to advance in terms of how research is conducted. Through the Stats/Methods program, grantees conduct research that helps applied researchers address challenges often encountered in education research, such as missing data, measurement error, small samples, the clustered nature of most group-design research, and the frequent phase shifts typically found in single-case research. Grantees have helped advance educational research by developing methods and guidelines for meta-analysis and systematic replication and are developing and evaluating AI and data science tools. Stats/Methods grants are unique in that they rarely involve collecting data from people and rely on secondary data, Monte Carlo simulations, mathematical derivations, and the creation of new software to refine and develop designs and analyses which applied researchers use for collecting, analyzing, and interpreting data from education settings.

Implications The methodological research supported by IES has made useful contributions to the field, including:

  • A substantial body of research spanning more than a decade on the use of value-added modeling in education;
  • Software (e.g., the Generalizer) that allows researchers to obtain intraclass correlations and other statistics useful for planning experiments, organized within grade level and school district;
  • Further development of the HLM software package, particularly its capacity to handle missing data imputation in multilevel models;
  • Advances in the application of inferential statistics to single-case data and development of effect size indices for single-case research, implemented in software such as ABk-power, singlecasemva, and PowerSCED;
  • Development of causal inference methods for RCTs as well as quasi-experimental designs, as implemented in packages including shinyRDD, KonFound-it!, flps, augsynth and balancer;
  • Theoretical and computational advances in measurement and the software available to analyze item responses such as bspam, regDIF and dynamicfit;
  • The development of Stan, a widely-used software package for Bayesian modeling, including multilevel modeling, and multilevel structural equation.

The 115 Stats/Methods grants have investigated a broad array of important topics, including estimation of treatment effect heterogeneity, additional advances in missing data imputation, continued development of effect size indices for single-case research, development of advanced IRT techniques which include projects with potential implications for NAEP, and advances in software for computing and interpreting statistical power analyses.

RELATED PROJECTS and PROGRAMS

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