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Policy Implications of Achievement Testing Using Multilevel Models: The Case of Brazilian Elementary Schools

Overview of attention for article published in Frontiers in Psychology, November 2016
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Title
Policy Implications of Achievement Testing Using Multilevel Models: The Case of Brazilian Elementary Schools
Published in
Frontiers in Psychology, November 2016
DOI 10.3389/fpsyg.2016.01727
Pubmed ID
Authors

Igor G. Menezes, Victor R. Duran, Euclides J. Mendonça Filho, Tainã J. Veloso, Stella M. S. Sarmento, Christine L. Paget, Kai Ruggeri

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.

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Mendeley readers

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 49 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 20%
Student > Ph. D. Student 9 18%
Student > Doctoral Student 7 14%
Student > Master 5 10%
Student > Bachelor 3 6%
Other 6 12%
Unknown 9 18%
Readers by discipline Count As %
Social Sciences 15 31%
Psychology 8 16%
Nursing and Health Professions 2 4%
Computer Science 2 4%
Mathematics 2 4%
Other 9 18%
Unknown 11 22%