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Factors that affect Students’ performance in Science: An application using Gini-BMA methodology in PISA 2015 dataset

Anastasia Dimiski ()
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Anastasia Dimiski: Department of Economics and Finance, University of Guelph, Guelph ON Canada

No 2004, Working Papers from University of Guelph, Department of Economics and Finance

Abstract: Existing theoretical and empirical evidence on the determinants of students’ performance is relatively short. Even more narrow is the literature that examines the impact of pre-primary education on students’ academic performance. Relying on the first-of-its-kind of the 2015 wave data from the Programme of International Student Assessment (PISA), the present study thoroughly discusses the associations between Students’ performance in Science and a set of variables that are classified into 14 categories, including attendance and non-attendance in pre-primary education. To implement this research question, Gini-BMA approach is employed, which accounts for theory uncertainty. It is found that, among the factors, attendance in pre-primary education (i.e. PC11) is a robust determinant of students’ performance in science. However, this result is supported only under the Gini methodology.

Keywords: students’ performance; pre-primary education; Gini regression coefficient; BMA methodology; PISA. (search for similar items in EconPapers)
JEL-codes: C11 C38 I21 J24 (search for similar items in EconPapers)
Pages: 32 pages
Date: 2020
New Economics Papers: this item is included in nep-edu
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