A Multilevel Analysis of Reading Literacy Achievement: Comparisons of the Canadian National Sample, and its Highest, and Lowest Quartiles

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dc.contributor.authorThomas, Shawn W.
dc.contributor.supervisorAnderson, John O.
dc.contributor.supervisorBoyer, Wanda Arleen Rumson
dc.date.accessioned2013-04-30T22:15:48Z
dc.date.available2013-04-30T22:15:48Z
dc.date.copyright2013en_US
dc.date.issued2013-04-30
dc.degree.departmentDepartment of Educational Psychology and Leadership Studies
dc.degree.levelMaster of Arts M.A.en_US
dc.description.abstractThis study investigates the importance of demographic variables and the influence of teachers on the reading literacy performance of Canadian 15-year-olds in a multi-level analysis of the national population as well as its highest and lowest quartiles. A large-scale representative dataset was chosen for these purposes. Multi-level modeling was completed using Hierarchical Linear Modeling (v. 6.08) quantifying the variance present at the student- and school-levels as well as identifying statistically significant correlates for each of the three models examined. Results were consistent with prior research while the use of a quartile-split accessed subpopulations based on achievement that are otherwise not closely examined by national averages. Students’ gender and schools’ SES appear to be the most influential individual factors of those examined, while the positive influence of teachers is a conclusion to be gleaned from this research.en_US
dc.description.proquestcode0535en_US
dc.description.proquestcode0533en_US
dc.description.proquestemailtheshawnwthomas@gmail.comen_US
dc.description.scholarlevelGraduateen_US
dc.identifier.urihttp://hdl.handle.net/1828/4578
dc.languageEnglisheng
dc.language.isoenen_US
dc.rights.tempAvailable to the World Wide Weben_US
dc.subjectdemographic variablesen_US
dc.subjectteachersen_US
dc.subjectliteracyen_US
dc.titleA Multilevel Analysis of Reading Literacy Achievement: Comparisons of the Canadian National Sample, and its Highest, and Lowest Quartilesen_US
dc.typeThesisen_US

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