The Impact of Early Childhood Education on Children's Non-Cognitive Outcomes

Jiarui Zhang, Uyen (Sophie) Nguyen, Zijian HuangCapstone Project Advisor: Professor Weinstein

Steinhardt School of Culture, Education, and Human Development12/14/2015

I. Background

II. Research Questions

III. Research Design & Method

IV. Main Findings

V. Limitations & Policy Implications

Presentation Overview

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● Landscape of Pre-K Education○ In 1960, 10% of 3- and 4-year-olds enrolled○ In 2005, 69% of all 4 year-olds nationwide○ In 2013-2014, state-funded pre-K served 1,347,272 children○ In 2013-2014, the total state funding increased to $5.6 billion

I. Background

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● Head Start○ Founded in 1965, a federally-funded early childhood education

program for low-income children under 5○ Designed to help break the cycle of poverty○ A comprehensive program to meet children’s emotional, social,

health, nutritional and psychological needs● Non-cognitive Skills

○ Definition○ Measurement ○ Importance

I. Background

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● Existing Studies on Head Start’s Impact○ Cognitive outcomes: clear○ Non-cognitive outcomes: mixed and not much

● Fade-out Effects○ Children’s cognitive outcomes will fade out around grade 3 or 4 in

elementary school.

I. Background

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● What is the impact of attending pre-school on students' non-cognitive outcomes?○ Specifically, Head Start vs other pre-k programs vs no pre-k

attendance● Do non-cognitive outcomes fade out as in the case of cognitive

outcomes? If so, when?

II. Research Questions

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● Data○ Early Childhood Longitudinal Study (ECLS-K: 98/99)○ Total number of observations: 21,409

● Sample○ Sampling frame: all U.S. public and private school students ○ Target sample: children from grade 3 to grade 8 who report their

pre-K education status and non-cognitive outcomes○ Sample restriction: pre-K education quality○ Final sample size: 13,117

III. Research Design & Method

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● Measure and Procedure○ For students: one-on-one assessments & questionnaires in

grade 3, 5, and 8○ For parents: computer-assisted telephone interviews &

questionnaires in kindergarten to grade 8○ For school administrators: self-administered paper

questionnaires in grade 5 to 8

III. Research Design & Method

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III. Research Design & Method

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● Treatment Group vs. Comparison Groups○ Children attended Head Start vs. children attended other pre-K

programs■ Other pre-K programs include day-care centers, preschool

centers, and nursery programs○ Children attended Head Start vs. children didn’t attend any pre-

K programs

III. Research Design & Method

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● Linear regression model○ Dependent variables (standardized)

■ Children’s internal scores in grade 3, 5, and 8■ Children’s external scores in grade 3 and 5

○ Key independent variable■ Head Start treatment

○ Covariates■ Individual characteristics■ Family characteristics■ Neighborhood characteristics

III. Research Design & Method

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Children’s internal scores in grades 3, 5, and 8

III. Research Design & Method

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original score Standardized score

Children’s external scores in grades 3 and 5

III. Research Design & Method

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original score Standardized score

Part of the descriptive statistics for the study

III. Research Design & Method

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Linear regression model:

Z represents Head Start treatmentT represents time dummy variables representing change of gradesX represents all other covariates

defines the Head Start children’s change from grade 3 to time point Tdefines the comparison group children’s change from grade 3 to T

So is the difference in difference

III. Research Design & Method

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Controlling for individual, family, and neighborhood characteristicsRobust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

IV. Main Findings: Internalizing Behavior Problems

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Regression Results Internal Scores

Variables Head Start vs. Other Pre-K Head Start vs. No Pre-K

Head Start -0.320*** (0.073) -0.213*** (0.082)

Grade 5 0.193*** (0.043) 0.246*** (0.057)

Grade 8 0.131*** (0.042) 0.298*** (0.055)

Head Start Grade 5 0.121 (0.092) 0.037 (0.104)

Head Start Grade 8 0.494*** (0.089) 0.309*** (0.100)

Constant -0.322 (0.205) -1.003*** (0.252)

N 11,538 7,008

IV. Main Findings: Internalizing Behavior Problems

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IV. Main Findings: Internalizing Behavior Problems

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IV. Main Findings: Externalizing Behavior Problems

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FINAL MODEL External Scores

Variables Head Start vs. Other Pre-K Head Start vs. No Pre-K

Head Start -0.128 (0.078) -0.092 (0.080)

Grade 5 0.198*** (0.045) 0.223*** (0.055)

Head Start Grade 5 -0.045 (0.096) -0.061 (0.104)

Constant -0.403* (0.231) -1.257*** (0.315)

N 7,713 4,679

Controlling for individual, family, and neighborhood characteristicsRobust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

IV. Main Findings: Externalizing Behavior Problems

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IV. Main Findings: Subgroup Analyses

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IV. Main Findings: Subgroup Analyses

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LOW-INCOME GROUP Internal Scores

Variables Head Start vs. Other Pre-K Head Start vs. No Pre-K

Head Start -0.133 (0.138) -0.338** (0.135)

Grade 5 0.297** (0.129) 0.181* (0.107)

Grade 8 0.416*** (0.141) 0.370*** (0.114)

Head Start Grade 5 0.078 (0.168) 0.147 (0.163)

Head Start Grade 8 0.190 (0.179) 0.260 (0.166)

Constant -0.621 (0.484) -1.234*** (0.581)

N 2,092 2,239

Controlling for individual, family, and neighborhood characteristicsRobust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

IV. Main Findings: Subgroup Analyses

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LOW-INCOME GROUP External Scores

Variables Head Start vs. Other Pre-K Head Start vs. No Pre-K

Head Start 0.004 (0.138) -0.195 (0.128)

Grade 5 0.315** (0.130) 0.171 (0.110)

Head Start Grade 5 -0.097 (0.175) 0.052 (0.163)

Constant -1.500** (0.700) -0.733 (0.773)

N 1,488 1,580

Controlling for individual, family, and neighborhood characteristicsRobust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

● Limitations○ Restriction of variables

■ Dependent variables■ Covariates

○ Assumptions of models■ Assumption for baseline covariates■ Assumption for other interventions

V. Limitations & Policy Implications

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● Policy Implications○ Revamping Head Start: more academic?

■ Non-cognitive skills as a mediator for cognitive outcomes○ Quality: practices that promote non-cognitive outcomes

V. Limitations & Policy Implications

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Questions?

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Q&A

Thank you for listening!

Contacts: Zijian Huang: zh620@nyu.edu

Uyen (Sophie) Nguyen: sophie.nguyen@nyu.eduJiarui Zhang: jz1874@nyu.edu

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