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Early Learning and Child Well-being
A Study of Five-year-Olds in England, Estonia, and the United States
The first five years of a child’s life is a period of great opportunity, and risk.
The cognitive and social-emotional skills that children develop in these early years
have long-lasting impacts on their later outcomes throughout schooling and adulthood.
The International Early Learning and Child Well-Being Study was designed to help countries
assess their children’s skills and development, to understand how these relate to
children’s early learning experiences and well-being. The study provides countries
with comparative data on children’s early skills to assist countries to better identify
factors that promote or hinder children’s early learning.
Three countries participated in this study in 2018: England (United Kingdom), Estonia
and the United States. The study directly assessed the emergent literacy and numeracy,
self-regulation and social-emotional skills of a representative sample of five-year-old
children in registered school and ECEC settings in each participating country. It
also collected contextual and assessment information from the children’s parents and
teachers. This report sets out the findings from the study as a whole.
The IELS database contains responses from individual children, teachers and parents in all participating countries. These data will be of use to statisticians and professional researchers who wish to undertake their own analysis of the IELS data. The data are available in SPSSTM, SASTM and csv files. Further information on the variables included in the database can be found in Chapter 16 of the study’s technical report.
The IEA International Database Analyzer (IDB Analyzer) is an application developed by the IEA Data Processing and Research Center (IEA-DPC) that can be used to analyse IELS data as well as data from other large-scale assessments. The IDB Analyzer is a Windows-based tool that creates SAS code or SPSS syntax to perform analyses with IELS data. The generated SAS code or SPSS syntax takes into account information from the sampling design in the computation of sampling variance and also handles the plausible values. The code generated by the IDB Analyzer can be used to compute descriptive statistics (e.g. percentages, averages), correlations and linear regression models. The tool allows for the testing of statistical hypotheses in the population without having to write any programming code.