Predicting Kindergarten Success for Economically Disadvantaged Head Start Children: A Latent Curve Analysis.Reportar como inadecuado




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The purpose of this study was to use data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-1999 database for public use (version 2.9.2.1; Westat, 2000) to examine a sample of Head Start children and families to predict kindergarten and first grade success, The study controlled family variables of income level, family structure, and parent education level while predicting kindergarten and first grade success. Both repeated measures analysis of variance and latent curve analysis (LCA) were used to predict the academic success of kindergarten and first grade children. Results show that both income level and parent education level had statistically significant (p<0.05) effects on reading, mathematics, and general knowledge item response theory (IRT) scale scores, while family structure had a much weaker effect (nonsignificant) on reading, mathematics, and general knowledge IRT scale scores. Further, the means of Head Start children from families at or above the poverty level were consistently higher than those of children from families below the poverty level. The study compared LCA model fit statistics for the models tested. The growth model used for reading appears to provide the best-fit statistics. The growth model for knowledge provides the second best-fit statistics. The growth model for mathematics fit well overall, although the fit statistics are not as ideal as the reading and knowledge growth models. More studies need to be done in that area. (Author/SLD)

Descriptors: Academic Achievement, Economically Disadvantaged, Grade 1, Kindergarten, Kindergarten Children, Longitudinal Studies, Prediction, Success











Autor: Jiang, Ying Hong; Mok, Doris; Weaver, Robert R.

Fuente: https://eric.ed.gov/?q=a&ft=on&ff1=dtySince_1992&pg=6166&id=ED482464







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