An analysis of factors affecting Mongolian students’ performance in science and mathematics: Evidence from PISA data

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Authors: Battsetseg Erdenebat, Bayarbat Ulziit
Cited by: 0

Abstract

This study analyzes Mongolian students’ performance in science and mathematics using the PISA-2022 dataset. It identifies the main influencing factors and aims to contribute to education policy and planning. The research objective is to determine which variables are significant predictors of science and mathematics performance, based on the student characteristics and test scores collected from Mongolian students in PISA. The dataset included more than 7,000 students from 196 schools representing 4 regions and 12 strata in Mongolia, taken from the publicly available PISA 2022 dataset. Data mining and quantitative analysis methods were applied using Python programming, and some statistical calculations and data handling were conducted with Microsoft Excel. The results show that mathematics performance is the strongest predictor of science achievement. Reading literacy is also a strong predictor of both science and mathematics, although its effect on science is weaker than that of mathematics. Mother’s education level, the number of digital devices, and the number of books at home have moderate to weak effects. Regional differences slightly affect performance in both science and mathematics, but the effect size is small and not practically significant.

Fields of Study & Subjects

School Choice and Performance Educational Outcomes and Influences Global Educational Policies and Reforms

Publication details

Journal / source
Asian Journal of Social Sciences and Management Studies
Volume
13
Issue
1
Pages
1–7
Publication date
9 January 2026