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An empirical approach is adopted in this paper to explore a possible model for prediction of students' science achievement in China and the United States. Construction of the model is based on the ninth-grade data base from Phase 2 of the Second International Education Association Science Study (SISS) in the United States and the SISS Extension Study (SES) in Hubei province in China. The common independent variables of science achievement are classified into gender, attitude, home background, classroom experience, and personal effort, according to the distinction between visible and latent characteristics and scree plots from principal-components analysis. Latent factors are represented by the first principal components in each of the four latent categories of student attitudes, home backgrounds, classroom experience, and personal effort. Predictors of the model are constructed by polynomials of the visible and latent factors and their interactions in a multivariate Taylor series. Significant predictors at the alpha=0.05 level are selected through a backward elimination procedure in the Statistical Analysis System. The structure of the four latent factors and the model complexity have been compared between the two countries in terms of their educational, political, social, and cultural contexts. Eight tables and two figures are included. (Contains 45 references.) (Author/SLD)

Descriptors: Academic Achievement, Background, Comparative Analysis, Context Effect, Cross Cultural Studies, Culture, Factor Analysis, Foreign Countries, High School Students, High Schools, International Studies, Models, Multivariate Analysis, Prediction, Science Achievement, Sciences, Sex Differences, Social Influences, Student Attitudes











Autor: Wang, Jianjun; Staver, John R.

Fuente: https://eric.ed.gov/?q=a&ft=on&ff1=dtySince_1992&pg=11283&id=ED367716







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