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Factors affecting students’ performance on national assessments of mathematics in Italy : a random forest approachDaniel Doz,
Bor Bregant, 2024, original scientific article
Abstract: This paper investigates the impact of teacher-assigned grades in Mathematics and Italian, students’ gender, and geographical macroregion on students’ performance in the Italian INVALSI mathematics assessment, using Random Forest analysis across grades 2, 5, 8, 10, and 13. Findings revealed that the two most influential factors are mathematics and Italian teacher-assigned grades, followed by gender. Boys consistently achieve higher INVALSI scores, while girls receive higher teacher-assigned grades. Performance disparities are observed among the five Italian geographic macroregions, with students from northern and central Italy performing better. Linguistic abilities and gender show varying significance across grades. The role of geographic macroregion is more pronounced in high school. Results were confirmed using Boosting Regression, validating the findings. This study highlights the significance of teacher-assigned grades, linguistic skills, gender, and geographic disparities in predicting students’ performance on the INVALSI mathematics test, showcasing the value of machine learning modelsin addressing educational equity.
Keywords: INVALSI, mathematics, national assessment, random forest, grades
Published in RUP: 22.01.2026; Views: 258; Downloads: 2
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