title: Policy Implications of Achievement Testing Using Multilevel Models: The Case of Brazilian Elementary Schools.
abstract: Large-scale educational assessment has been established as source of descriptive, evaluative and interpretative information that influence educational policies worldwide throughout the last third of the twentieth century. In the 1990s the Brazilian Ministry of Education developed the National Basic Education Assessment System (SAEB) that regularly measures management, resource and contextual school features and academic achievement in public and private institutions. In 2005, after significant piloting and review of the SAEB, a new sampling strategy was taken and Prova Brasil became the new instrument used by the Ministry to assess skills in Portuguese (reading comprehension) and Mathematics (problem solving), as well as collecting contextual information concerning the school, principal, teacher, and the students. This study aims to identify which variables are predictors of academic achievement of fifth grade students on Prova Brasil. Across a large sample of students, multilevel models tested a large number of variables relevant to student achievement. This approach uncovered critical variables not commonly seen as significant in light of other achievement determinants, including student habits, teacher ethnicity, and school technological resources. As such, this approach demonstrates the value of MLM to appropriately nuanced educational policies that reflect critical influences on student achievement. Its implications for wider application for psychology studies that may have relevant impacts for policy are also discussed.
authors.affiliation: Laboratory of Quantitative, Methods for Predictive Psychometrics, Psychology Institute, Federal University of BahiaSalvador, Brazil; Judge Business School, University of CambridgeCambridge, UK.
authors.forename: Igor G
authors.initials: IG
authors.lastname: Menezes
authors.affiliation: Laboratory of Quantitative, Methods for Predictive Psychometrics, Psychology Institute, Federal University of Bahia Salvador, Brazil.
authors.forename: Victor R
authors.initials: VR
authors.lastname: Duran
authors.affiliation: Laboratory of Quantitative, Methods for Predictive Psychometrics, Psychology Institute, Federal University of Bahia Salvador, Brazil.
authors.forename: Euclides J
authors.initials: EJ
authors.lastname: Mendonça Filho
authors.affiliation: Laboratory of Quantitative, Methods for Predictive Psychometrics, Psychology Institute, Federal University of Bahia Salvador, Brazil.
authors.forename: Tainã J
authors.initials: TJ
authors.lastname: Veloso
authors.affiliation: Laboratory of Quantitative, Methods for Predictive Psychometrics, Psychology Institute, Federal University of Bahia Salvador, Brazil.
authors.forename: Stella M S
authors.initials: SM
authors.lastname: Sarmento
authors.affiliation: Department of Education, University of Oxford Oxford, UK.
authors.forename: Christine L
authors.initials: CL
authors.lastname: Paget
authors.affiliation: Policy Research Group, Department of Psychology, University of Cambridge Cambridge, UK.
authors.forename: Kai
authors.initials: K
authors.lastname: Ruggeri
keywords: Brazilian education system; education policies; hierarchical linear modeling; large-scale educational assessment; school achievement