{"title":"Predicting the mathematics pathways of english language learners: a multilevel analysis","authors":"Cristina Runnalls","doi":"10.51272/PMENA.42.2020-65","DOIUrl":null,"url":null,"abstract":"This study employed hierarchical linear modeling to investigate the studentand school-level factors associated with the secondary mathematics achievement of English language learners (ELLs) and non-ELL students among a nationally representative sample of ninth graders in the United States. While certain characteristics, such as socioeconomic status, attitudes and interest in mathematics, and school engagement and belonging were predictive of access to and achievement in mathematics for both student groups, the direction and relative magnitude of the predictors differed. School-level variables, such as whether the school was public or private and administrator perceptions of school climate, were only predictive of mathematics grade point average (GPA) for non-ELLs. Implications of the findings are discussed.","PeriodicalId":68089,"journal":{"name":"数学教学通讯","volume":"41 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"数学教学通讯","FirstCategoryId":"1089","ListUrlMain":"https://doi.org/10.51272/PMENA.42.2020-65","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This study employed hierarchical linear modeling to investigate the studentand school-level factors associated with the secondary mathematics achievement of English language learners (ELLs) and non-ELL students among a nationally representative sample of ninth graders in the United States. While certain characteristics, such as socioeconomic status, attitudes and interest in mathematics, and school engagement and belonging were predictive of access to and achievement in mathematics for both student groups, the direction and relative magnitude of the predictors differed. School-level variables, such as whether the school was public or private and administrator perceptions of school climate, were only predictive of mathematics grade point average (GPA) for non-ELLs. Implications of the findings are discussed.