IBSS: The Levels and Timing of Family and School Influences on Children's Development

University Of Texas At Austin, Austin TX

Investigators

Abstract

This interdisciplinary research project will identify the optimal levels and timing of key aspects of the two most important contexts in children's lives -- their families and their schools -- for the development of children from birth through their transition to adulthood. The project will draw on and contribute new fundamental knowledge that bridges a broad range of fields, including developmental psychology, sociology, demography, sociology of education, educational psychology, and economics. The project will yield new insights regarding developmental transitions precipitate continuity or discontinuity in development across the early life course, with equal emphasis placed on children who experience continuity in development as on children who experience discontinuity. By enhancing basic understanding of the complex interactions among children, their families, their schools, and other contextual factors, the project will inform the design of interventions to address problems experienced by some children and more effectively guide the use of public dollars toward the most efficient times for interventions. The investigators will focus on three ways of characterizing the influence of family and school contexts on child and youth development: sensitive periods, tipping points, and transitions. Sensitive periods refer to the times in development that are most susceptible to contextual influence and are most effective for predicting future functioning. Tipping points are the levels at which a contextual influence affects accelerated or diminishing returns. Transitions are major changes in a context that can affect changes in the individual. The investigators will analyze data from six national longitudinal datasets that cover multiple stages of the early life course as well as three experimental datasets that will permit them to draw stronger conclusions about causal relationships. The team will implement cutting-edge statistical methods that adhere to the best practices across disciplines. Throughout the project, the investigators will use the best available measurements to examine each part of the conceptual model, replicate models across datasets and cohorts as a means of increasing confidence in results, leverage state-of-the-art methods to capture the dynamic nature of individual development, and consider alternative explanations and specifications in order to increase confidence in causal inferences. This project is supported through the NSF Interdisciplinary Behavioral and Social Sciences Research (IBSS) competition.