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ERIC ED512707: Using Meta-Analysis to Explain Variation in Head Sta...
by ERIC
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Head Start was designed as a holistic intervention to
improve economically disadvantaged, preschool-aged
children's cognitive and social development by providing
a comprehensive set of educational, health, nutritional,
and social services, as well as opportunities for parent
involvement (Zigler & Valentine, 1979). Given the current
interest in ECE (early childhood education) as an
intervention strategy for disadvantaged children and the
magnitude of public investment in Head Start ($6.9
billion in FY 2007), it is important for researchers and
policy makers to be effective designers and consumers of
Head Start evaluations (Office of Head Start, 2008).
Although some previous meta-analyses suggest a link
between evaluation characteristics and results, evidence
is mixed, and recent methodological advances have not
been considered. A more detailed empirical test of the
contribution of particular research design
characteristics is needed to enable scholars to better
understand findings from prior studies, as well as to
inform future studies. This study investigates the role
of such factors in explaining variation in Head Start
evaluation results for children's cognitive and
achievement outcomes. Specifically, the authors test
whether the following research design characteristics
explain heterogeneity in the estimated effects of Head
Start on children's cognitive and achievement outcomes:
type and rigor of design, quality of dependent measure,
attrition, and activity level of control group. Although
the authors are still completing coding for some Head
Start studies that will ultimately be included in their
final analyses, preliminary examination of the available
data reveals interesting variation along methods-related
characteristics between contrasts. For example, they see
substantial variation in the activity level of the
control group; type of research design; whether baseline
equivalency was tested, and if so, whether significant
differences between groups were detected; and whether
other sources of bias were detected by coders. Additional
variation in the type and reliability of dependent
measures, timing of tests, and attrition was also
detected at the effect size level. (Contains 2 tables.)
Date Published: 2016-02-01 04:00:26
Identifier: ERIC_ED512707
Item Size: 7064377
Language: english
Media Type: texts
# Topics
ERIC Archive; Intervention; Early Chi...
# Collections
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