Factors Associated with Mathematics Performance in Brazilian Basic Education
Abstract Several studies have indicated that student performance is strongly influenced by school context. Within this frame of reference, the present study sought to identify contextual variables that affect proficiency in mathematics taking the multilevel structure of schools into consideration. The information of 4,338,885 students who participated in the Brazilian national assessment of educational progress of 2009 was used. Multilevel analysis showed an intra-class correlation of .27 and .19 for the 5th grade of elementary school and 9th grade of middle school, the last year of middle school. In both models, more than 50% of school level variance and more than 11% of the variance on student level was explained. The final model is composed of control variables, 13 student level variables, 9 school level variables, and random and interaction effects. The results contribute to a better comprehension of factors that affect school performance, which permits the orientation of public policies.
| Main Authors: | , , |
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| Format: | Digital revista |
| Language: | English |
| Published: |
Universidade de São Francisco, Programa de Pós-Graduação Stricto Sensu em Psicologia
2016
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| Online Access: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-82712016000100087 |
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| Summary: | Abstract Several studies have indicated that student performance is strongly influenced by school context. Within this frame of reference, the present study sought to identify contextual variables that affect proficiency in mathematics taking the multilevel structure of schools into consideration. The information of 4,338,885 students who participated in the Brazilian national assessment of educational progress of 2009 was used. Multilevel analysis showed an intra-class correlation of .27 and .19 for the 5th grade of elementary school and 9th grade of middle school, the last year of middle school. In both models, more than 50% of school level variance and more than 11% of the variance on student level was explained. The final model is composed of control variables, 13 student level variables, 9 school level variables, and random and interaction effects. The results contribute to a better comprehension of factors that affect school performance, which permits the orientation of public policies. |
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