A Cross-national Study of Mathematics Achievement Via Three-level Multilevel Models

The present study explored the effects of the national and cultural contexts on students' mathematics achievement. The study also investigated the nature and magnitude of student-level (level 1), school-level (level 2), and country-level (level 3) factors that are associated with math achievement. The Program for International Student Assessment (PISA) 2018 datasets were used. The main predictors focusing on this study included university admission procedure and the country's culture of mindsets about intelligence at level 3, indicating extra-curricular activities at level 2, growth mindset, and resilience self-efficacy at level 1. Other than main predictors, various predictors including country's characteristics, school characteristics, school climate factors, students' demographic characteristics, and non-cognitive abilities were added in the analysis to examine the main predictors are statistically significant after controlling for other predictors. The findings of HLM analysis showed that mathematics achievement is associated with national and cultural contexts since the study found 31.30% of the total variation was accounted for level 3 in math achievement. Also, the significant findings of the study indicated that university admission procedure was significantly associated with country-mean math achievement while the country's culture of mindsets about intelligence was not at level 3. At level 2, providing extra-curricular activities in school was a significant predictor for math achievement. At level 1, a growth mindset and information and Communication Technology (ICT) usage were positively associated with math achievement. The other significant predictors for math achievement were found in the model. In addition, the study found that the compositional effect of ICT usage explained a significant amount of between schools and countries variance even after controlling for other predictors in the analysis. Moreover, the study found several counterintuitive association phenomena due to shift of meaning. These findings were explained in terms of practical and theoretical implications for policymakers, educators, and researchers to improve students' mathematics achievement.

Name thesis:degree_name

Doctor of Philosophy

Level thesis:degree_level

doctoral

Discipline thesis:degree_discipline

Educational Research and Evaluation

Department dc:contributor.department

Educational Research and Evaluation

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2023

Author dc:creator

• Lee, Youjin

Chair dc:contributor.committeechair

• Miyazaki, Yasuo

Committee members dc:contributor.committeemember

• Jones, Brett D.
• Skaggs, Gary E.
• Kniola, David J.

• Mathematics Achievement
• Hierarchical Linear Modeling (HLM)
• Growth Mindset
• Information and Communication Technology (ICT)

Statement dc:rights

• Creative Commons Attribution-NonCommercial 4.0 International

Licence dc:rights.uri

• http://creativecommons.org/licenses/by-nc/4.0/

Language dc:language.iso

en

Dc Identifier Other

vt_gsexam:36056

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/113244