Developmental Sciences

The Developmental Sciences program, administered by the Division of Behavioral and Cognitive Sciences within the National Science Foundation (NSF), supports basic research on human development across the lifespan. The program resides within the Directorate for Social, Behavioral and Economic Sciences and is focused on enhancing our understanding of perceptual, cognitive, linguistic, social, cultural, and biological processes that contribute to individual development. The NSF was established to promote scientific progress and has long been a key source of federal funding for foundational research in a wide array of scientific domains, including human development. This grant program seeks to fund projects that explore developmental processes in domains such as perception, cognition, emotion, social behavior, language acquisition, and motor skills. Eligible studies may span various stages of life, from infancy to old age, and can include non-human animal populations where appropriate. The program places particular emphasis on research that investigates the influences of family, community, culture, media, genetics, and biological systems on developmental change. Multidisciplinary, multi-method, and longitudinal research designs are highly encouraged, as are studies that integrate across different analytical levels and timescales to uncover the mechanisms and processes that underlie human development. Awards under this program typically range from $100,000 to $200,000 annually for a three-year period, with total project budgets generally falling between $200,000 and $600,000. Proposals exceeding this typical range may be returned without review. Conference or workshop proposals, limited to around $35,000, are considered on a case-by-case basis and require prior invitation from a program director. Supplemental funding is available through additional NSF mechanisms, such as Research Experiences for Undergraduates (REU), Career-Life Balance, and others, all of which must be pre-approved by program officers. Applications may be submitted by a broad range of organizations, including two- and four-year U.S. institutions of higher education (IHEs), non-profit and for-profit research institutions, state and local governments, tribal nations, and federally recognized tribal organizations. Foreign collaborations are allowed, but NSF funding will only support the U.S. portion of the project. Proposals must be submitted via Research.gov or Grants.gov and must conform to the guidelines provided in the NSF Proposal & Award Policies & Procedures Guide (PAPPG). While no letters of intent or preliminary proposals are required, applicants are encouraged to submit a one-page project summary for preliminary feedback. Evaluation of proposals is based on NSF’s core merit review criteria: intellectual merit and broader impacts. Intellectual merit assesses the potential to advance knowledge in developmental science, while broader impacts evaluate the societal relevance and potential benefits of the proposed research. Successful applications will address equity-centered collaboration, transparency in sampling decisions, constraints on generalizability, and data-sharing plans. Cultural competence and inclusion of underrepresented groups in both research participation and team composition are strongly encouraged. The Developmental Sciences program offers two deadlines per year: January 30 and July 30, with these dates recurring annually. Given the recurring nature of the program, the next expected submission opportunity is July 30, 2026. Program contacts include Anna V. Fisher ([email protected]), Joseph C. Toscano ([email protected]), and Katia McCuen ([email protected]). Applicants are advised to ensure IRB or IACUC approvals are in place before funding is finalized if the research involves human or animal subjects. Annual and final reporting requirements include updates on data management, broader impacts, and training activities. The anticipated total program funding is approximately $6.5 million, with an estimated 12 awards per year.

Prioritize intellectual merit and societal relevance; demonstrate equity-centered collaboration; justify sample composition and generalizability; adhere to FAIR data principles