Understanding the Disparities in Mathematics Performance: An Interpretability-Based Examination
Ismael Gomez-Talal, Luis Bote-Curiel, Jose Luis Rojo-Alvarez

TL;DR
This study uses interpretability models on PISA data to identify key factors like socioeconomic status, gender, and geography that contribute to disparities in students' Mathematics performance worldwide.
Contribution
It applies advanced interpretability techniques to large-scale educational data, revealing complex factors behind performance disparities and offering insights for targeted interventions.
Findings
Lower socioeconomic status correlates with lower performance.
Regional disparities significantly affect Mathematics scores.
Gender differences influence performance patterns across regions.
Abstract
Problem. Educational disparities in Mathematics performance are a persistent challenge. This study aims to unravel the complex factors contributing to these disparities among students internationally, with a focus on the interpretability of the contributing factors. Methodology. Utilizing data from the Programme for International Student Assessment (PISA), we conducted rigorous preprocessing and variable selection to prepare for applying binary classification interpretability models. These models were trained using the Stratified K-Fold technique to ensure balanced representation and assessed using six key metrics. Solution. By applying interpretability models such as Shapley Additive Explanations (SHAP) analysis, we identified critical factors impacting student performance, including reading accessibility, critical thinking skills, gender, and geographical location. Results. Our…
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