{"title":"考察爱尔兰小学后学生在数学和科学方面的高成绩:PISA数据的多水平二元逻辑回归分析","authors":"Vasiliki Pitsia","doi":"10.1186/s40536-022-00131-x","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":37009,"journal":{"name":"Large-Scale Assessments in Education","volume":" ","pages":"1-30"},"PeriodicalIF":2.6000,"publicationDate":"2022-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Examining high achievement in mathematics and science among post-primary students in Ireland: a multilevel binary logistic regression analysis of PISA data\",\"authors\":\"Vasiliki Pitsia\",\"doi\":\"10.1186/s40536-022-00131-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":37009,\"journal\":{\"name\":\"Large-Scale Assessments in Education\",\"volume\":\" \",\"pages\":\"1-30\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2022-09-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Large-Scale Assessments in Education\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1186/s40536-022-00131-x\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"EDUCATION & EDUCATIONAL RESEARCH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Large-Scale Assessments in Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/s40536-022-00131-x","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
Examining high achievement in mathematics and science among post-primary students in Ireland: a multilevel binary logistic regression analysis of PISA data