Why East Asian students perform better in mathematics than their peers: An investigation using a machine learning approach

31 Pages Posted: 2 Aug 2021

See all articles by Hanol Lee

Hanol Lee

Southwestern University of Finance and Economics

Jong-Wha Lee

Korea University

Date Written: July 30, 2021

Abstract

Using a machine learning approach, we attempt to identify the school-, student-, and country-related factors that predict East Asian students’ higher PISA mathematics scores compared to their international peers. We identify student- and school-related factors, such as metacognition–assess credibility, mathematics learning time, early childhood education and care, grade repetition, school type and size, class size, and student behavior hindering learning, as important predictors of the higher average mathematics scores of East Asian students. Moreover, country-level factors, such as the proportion of youth not in education, training, or employment and the number of R&D researchers, are also found to have high predicting power. The results also highlight the nonlinear and complex relationships between educational inputs and outcomes.

Keywords: education, East Asia, machine learning, mathematics test score, PISA

JEL Classification: C53, C55, I21, J24, O15

Suggested Citation

Lee, Hanol and Lee, Jong-Wha, Why East Asian students perform better in mathematics than their peers: An investigation using a machine learning approach (July 30, 2021). CAMA Working Paper No. 66/2021, Available at SSRN: https://ssrn.com/abstract=3896033 or http://dx.doi.org/10.2139/ssrn.3896033

Hanol Lee

Southwestern University of Finance and Economics ( email )

55 Guanghuacun St,
Chengdu, Sichuan 610074
China

Jong-Wha Lee (Contact Author)

Korea University ( email )

Anam-dong, Sungbuk-Ku
Dept. of Economics
Seoul, 136-701
82-2-3290-2216 (Phone)
82-2-928-4948 (Fax)

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