A sensibilidade do Ideb a variáveis educacionais avaliada por um modelo matemático

• Autor(a) principal: Matheus, Natália de Mesquita
• Data de Publicação: 2015
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da PUC_SP
• Texto Completo: https://tede2.pucsp.br/handle/handle/16174
• topic: Política educacional; Avaliação educacional; Ideb; Índice de Desenvolvimento da Educação Básica; Modelo matemático; Análise do comportamento; Educational policy; Educational assessment; CHAID; Chi-squared Automatic Interaction Detector; Mathematical model; Behavior analysis; CNPQ::CIENCIAS HUMANAS::EDUCACAO::FUNDAMENTOS DA EDUCACAO::PSICOLOGIA EDUCACIONAL

The present study aimed at evaluating the functionality of CHAID to analyze educational data by demonstrating Ideb s sensitivity to different aspects of educational system. The dependent variables were Ideb 2011 from initial and final series of the elementary years; the independent variables were considered separately in a multilevel analysis. At the first level, considered independent variable were the cities former performance measured by the Ideb at 2005, 2007 and 2009; at the second level, the cities budget with education, such as student cost and the percentage of investments at basic education, and others came into focus; and, at the third level, the independent variables considered were demographic data such as region, State, index of human development and influence region. The results shown at the first level indicate a direct relationship between higher scores at the dependent variable and at former performance. Most of the cities with higher scores in 2009 showed higher scores at the Ideb in 2011 and those cities with lower scores in former performances (in 2009, 2007 and, some cases even in 2005) showed lower scores in 2011. At the second level, the results indicate that the effects produced by most recent expenditure (from 2011) are less relevant than those expended earlier (in 2009). Those data suggest that the effects from financial investments in education are / will probably be seen at medium or long term. At the third level, the State was a more significant variable than region and the other tested variables. Statistical algorithms CHAID and exhaustive-CHAID showed to be effective to identify significant variables related to academic performance measured by Ideb, with the production of comprehensive information without losing the specifies of each reality. However, exhaustive-CHAID, turned out to be a more rigorous than CHAID in the selection of variables. It was demonstrated that the multilevel analysis produced different results whern compared with the comprehensive analysis. It suggests an important effects from the interaction among all tested variables. The availability of educational data for identification and analysis of relationships between political actions and its educational outcomes is discussed. Finally,, the contributions of behavior analysis to the interpretation and analysis of people involved at educational policy behavior are considered