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  • 标题:Language and Literacy Profiles: A Mixture Modeling Approach
  • 本地全文:下载
  • 作者:Julia Lee Ai Cheng ; Julia Lee Ai Cheng ; Stephanie Al Otaiba
  • 期刊名称:Procedia - Social and Behavioral Sciences
  • 印刷版ISSN:1877-0428
  • 出版年度:2013
  • 卷号:97
  • 页码:114-121
  • DOI:10.1016/j.sbspro.2013.10.211
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractMixture modeling was used to examined the: (a) heterogeneity and prevalence of the language and literacy profiles among 521 first grade students (Malaysian equivalent of Primary 1) and (b) predictors that optimize the classification of language and literacy profiles. Based on the Simple View of Reading as a theoretical framework, five language and literacy profiles were identified. These were students with: a) the weakest performance on average in literacy but slightly higher language skills, b) weak performance in both language and literacy, c) average performance in language and literacy, d) above average performance on language and literacy, and e) the strongest performance in language and literacy. Unique predictors of class membership differentiation for all groups were phonological awareness, teacher judgment on academic achievement, and socioeconomic status.
  • 关键词:Mixture Modelling;Latent Profiles;Language;Literacy;First Grade
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