ECR’s Building Capacity in STEM Education Research (ECR: BCSER) supports projects that build investigators’ capacity to carry out high-quality STEM education research that will enhance the nation’s STEM education enterprise. In addition, ECR: BCSER seeks to broaden the pool of researchers who can advance knowledge regarding STEM learning and learning environments, broadening participation in STEM fields, and STEM workforce development. 

Specifically, ECR: BCSER supports activities that enable researchers to expand their areas of expertise and acquire the requisite knowledge and skills to conduct rigorous research in STEM education. Career development may be accomplished through investigator-initiated professional development and research projects or through institutes that enable researchers to integrate methodological strategies with theoretical and practical issues in STEM education.

To successfully conceptualize, design, and execute studies capable of making contributions to knowledge in STEM education and learning, broadening participation, and workforce development, investigators and their teams typically require a wide range of knowledge, skills, expertise, and experiences. Examples of relevant capacity-building foci span a range of topics including but not limited to:

• Deep knowledge of subject-matter literature: Domain expertise (mastery of theories and findings) is critical to investigators’ ability to identify important scientific questions and articulate a theoretically derived and framed rationale for the project.
• Interdisciplinary perspectives: Theories, methodologies, analytical techniques, and findings that can have a catalytic effect when explored in the context of multiple fields. Moreover, interdisciplinary endeavors also increase the human capacity of the nation to address problems, broadening the range and diversity of scholars working toward their solutions.
• Skill operationalizing research questions and articulating theories of change: Investigators should be able to operationalize the conceptual framework that organizes the responses to the research questions before collecting data, e.g., reducing variables into measurable factors.
• Expertise in study design, research methods, and data analysis techniques and familiarity with advances in computational, quantitative, qualitative, and evaluative research methodologies: Expertise in these areas is essential in arguing the feasibility and appropriateness of the proposed research to generate sufficiently robust evidence on the topic(s) of interest and in executing the study as planned. Depending upon the nature of the research proposed, experience may be required to identify appropriate measures, devise appropriate sampling strategies, develop and establish the psychometric properties of research instruments, and align analytic methods with the study design.
• Expertise that could advance educational innovation: Investigators should be able to incorporate new methods and techniques in their research that will improve education quality. For example, they may consider how artificial intelligence tools or large data sets could be used or mined to enhance traditional teaching and learning methods. Areas where this research may be applicable include intelligent tutoring systems, personalized learning, computer-adapted assessments, or in automating of teaching tasks.
• Skill synthesizing study findings through meta-analysis, meta-synthesis, and other systematic review methodologies.
• Experience collecting, managing, documenting, and archiving data (e.g., to facilitate replication and reproducibility studies and secondary analyses).
• Experience building teams, establishing partnerships, leading collaborations, and mentoring junior collaborators.

For information related to proposal types, see: https://www.nsf.gov/pubs/2022/nsf22548/nsf22548.pdf#page=4

• Others (see text field entitled "Additional Eligibility Criteria" for clarification)

Estimated Total Program Funding: