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IES Grant

Title: Kids Integrated Data System (KIDS): An Evidence-Based System for Enhancing Educational Proficiency and Social Adjustment
Center: NCER Year: 2008
Principal Investigator: Fantuzzo, John Awardee: University of Pennsylvania
Program: Improving Education Systems      [Program Details]
Award Period: 2 years Award Amount: $699,999
Type: Exploration Award Number: R305A080309
Description:

Purpose: This research project is designed to examine what, how, when, and where early biological and social risk factors impede the development of educational competencies for an entire population of third-grade students in a large, economically distressed urban city. The project will also test the utility of the Kids Integrated Data System (KIDS), which merges administrative data from children's birth records, physical and mental health service utilization records, Medicaid eligibility, homelessness and child welfare services, and public school education records to provide unique and detailed information concerning students' eventual academic proficiency and social adjustment.

Project Activities: For this study, educational records from the school district will be integrated with biological administrative data on birth risks, poverty, low maternal education, maternal depression, homelessness, and child maltreatment. Analyses will estimate the relationship of these risk factors with third-grade standardized reading and mathematics achievement, classroom behavioral adjustment, and attendance.

Products: Products from this project include published reports on the utility of a large, cross-agency, integrated database to provide unique and detailed information concerning students' eventual academic proficiency and social adjustment, as well as reports on the relationships between a variety of biological and social risk factors and third-grade attendance, academic achievement, and behavioral adjustment.

Structured Abstract

Setting: The participating schools are located in the School District of Philadelphia, Pennsylvania.

Population: This study will include over 10,000 third-grade students drawn from the School District of Philadelphia.

Intervention: KIDS was established to provide policymakers the capacity to respond directly to community-based needs through population-based inquiry. KIDS data are collected annually from the school district and each major public service agency in the city that serves children and families and currently include longitudinal, archival records from 1990 to 2006. This study utilizes KIDS to examine the relationships between a variety of biological and social risk factors and third-grade attendance, academic achievement, and behavioral adjustment.

Research Designs and Methods: The study is based on a statistical analysis of an existing dataset. Educational records from the school district will be integrated with biological birth risks, poverty, low maternal education, maternal depression, homelessness, and child maltreatment. The first phase of the study will involve the preparation of the integrated dataset. Phase 2 will involve statistical analyses. Phase 3 will focus on the dissemination of findings to relevant policymakers to gain a fuller understanding of the findings. The final phase will involve conceptualizing a viable (e.g., cost-effective and sustainable) systems intervention that will enable educational policymakers to mitigate the effects of early risk factors on third-grade proficiency and social adjustment.

Key Measures: First-, second-, and third-grade standardized reading and mathematics achievement, classroom behavioral adjustment, and attendance will be the primary outcomes for this study. No Child Left Behind state third-grade assessments will be used to indicate reading and mathematics proficiency.

Data Analytic Strategy: Researchers will use multivariate statistical analysis. Multilevel modeling will address clustering of children within classrooms and schools. Multilevel multiple logistic regression models will examine the added likelihood of experiencing a poor educational outcome in the third grade having previously been exposed to biological and social risk factors. Researchers will also use multilevel generalized linear growth modeling to determine how students' individual growth trajectories for literacy, mathematics, school attendance, and classroom behavior (a) vary as related to whether or not students meet state proficiency standards at the end of third grade and (b) vary as a function of social and biological risk factors. Multilevel generalized linear growth modeling and repeated multilevel logistic regression modeling with receiver operating curve analyses will be used to conduct analyses of the timing of detecting early risk effects on the trajectory of longitudinal outcomes. Geographic information systems (GIS) analyses and multilevel cross-classification multiple logistic regression modeling will be used to map the dispersion of risks and determine the relative contribution of risks aggregated at the school and neighborhood levels in order to strategically inform the distribution of relevant educational and child and family municipal services.

Publications

Journal article, monograph, or newsletter

Fantuzzo, J., LeBoeuf, W., Rouse, H., & Chen, C. C. (2012). Academic Achievement of African American Boys: A City-Wide, Community-Based Investigation of Risk and Resilience. Journal of School Psychology, 50 (5): 559–579.

Fantuzzo, J., Perlman, S., and Dobbins, E. (2011). Types and Timing of Child Maltreatment and Early School Success: A Population-Based Investigation. Children and Youth Services Review Special Issue on the Maltreatment of Young Children, 33 : 1404–1411.

LeBoeuf, W.A., Fantuzzo, J.W., and Lopez, M.L. (2010). Measurement and Population Miss-Fits: A Case Study on the Importance of Using Appropriate Measures to Evaluate Early Childhood Interventions. Applied Developmental Science, 14 (1): 45–53.

Perlman, S., and Fantuzzo, J. (2010). Timing and Influence of Early Experiences of Child Maltreatment and Homelessness on Children's Educational Well-Being. Children and Youth Services Review, 32 (2): 874–883.

Rouse, H.L., Fantuzzo, J.W., and LeBoeuf, W. (2011). Comprehensive Challenges for the Well Being of Young Children: A Population-Based Study of Publicly Monitored Risks in a Large Urban Center. Child and Youth Care Forum, 40 (4): 281–302.

** This project was submitted to and funded under Education Policy, Finance, and Systems in FY 2008.


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