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The multilevel value added approach to measuring school effectiveness is now widely used. We propose a method to adjust for measurement error to investigate the extent to which this changes school effect estimates. It is applied to longitudinal data collected in the region of Cova da Beira (NUT III) for 1st, 3rd, 5th, 7th and 8th grades. Three different variance component models are considered, depending on the predictor variables included. Assuming measurement error occurs in explanatory and/or response variables, corrections are made for different values of the coefficient of reliability. Moreover, models are fitted under the assumption of either independent or correlated measurement errors.

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The main goal of this study is to show that the association between university entrance score and first-year students' academic performance varies randomly across courses after controlling for students' sociodemographic, schooling trajectory and motivational variables. The sample consists of 2697 first-year students who were enrolled in 54 courses at a Portuguese public university in 2015/16. Multilevel modelling of academic performance suggests that 34% of variability in grade point average is due to differences among courses and that 80% of such variability is explained by the field of study, whether the university is the student's first choice, and the student's gender, age and parents' level of education. In addition, the results corroborate that the university entrance score is the strongest predictor of first-year academic performance.

<span style="font: 13px/normal verdana, arial; color: #000000; text-transform: none; text-indent: 0px; letter-spacing: normal; word-spacing: 0px; float: none; display: inline !important; white-space: normal; background-color: #ffffff;">Os autores, no seu importante trabalho, procuram demonstrar as potencialidades da adoção de modelos de regressão linear multilevel na análise e modelagem de dados da avaliação educacional, em oposição aos modelos de regressão linear clássicos impróprios para tratar dados com estrutura hierárquica. Ao final, fazem uma aplicação de dois níveis aos dados de Matemática do SAEB - Sistema de Avaliação da Educação Básica, de 1997, relativos à 8ª série do ensino fundamental da Região Sudeste do país.</span>

Based on an intergenerational perspective, the study examines the mitigation of the inequalities in the distribution of education, taking into consideration the relationships between educational achievements and socio-demographic attributes such as socioeconomic status and race/color. The research uses ENEM data and the observations spans from 2009 to 2012. In order to examine the educational inequalities, the analysis explores the Gini coefficient, the Lorenz curve and multilevel modeling data for the year 2012. Using the level of education, as well as the ENEM’s test scores, the evidence suggests the reduction of intergenerational inequalities in the distribution of education. In addition, the results indicate that educational performance is sensitive to socio-spatial and race-related variables. The multilevel analysis allowed the decomposition of the variance of educational outcomes at the pre-university level and for different UF's. Such approach reveals that the variability of results at the intra-municipal level is greater than at the inter-municipal setting. Moreover, empirical evidences indicates the existence of substantial performance variability among schools, suggesting that either schools or municipalities are relevant units for educational policies. The reduction of these disparities must be considered a priority issue. Additional research related to determinants of school effect, considering intra and extra-school dimensions, and educational effectiveness-oriented policies is needed.

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RESUMO O artigo apresenta e debate as análises de valor acrescentado, eficácia diferencial e equidade social realizadas através da aplicação de modelo multinível (UF, município, escola, aluno) aos dados longitudinais de estudantes que fizeram a Prova Brasil 2011, no 5 o ano, e a Prova Brasil 2015, no 9 o ano do ensino fundamental. Estimou-se a contribuição da escola brasileira em três dimensões: promoção da aprendizagem em Língua Portuguesa e Matemática, no período de 2011 a 2015 (valor acrescentado); influência diferenciada nas aprendizagens ocorridas durante o período em análise, tendo como referência o nível de conhecimento dos alunos à entrada, no 5º ano (eficácia diferencial); e influência diferenciada nas aprendizagens ocorridas durante esse período, tendo como referência o nível socioeconômico dos alunos (equidade social). Foram testadas ainda variáveis sociodemográficas do aluno, tais como sexo, cor/raça, situação face ao trabalho e se a mãe é ou não alfabetizada. O artigo apresenta resultados inovadores de eficácia educacional no Brasil, mostrando que, ao contrário do que consta na literatura internacional, a magnitude do indicador de valor acrescentado é similar à encontrada em estudos em países desenvolvidos. Os resultados confirmam o conhecimento acumulado sobre o desempenho escolar dos alunos por nível socioeconômico, sexo e cor/raça.