The Determinants of Mathematics Achievement: A Gender Perspective Using Multilevel Random Forest

Alice Bertoletti, Marta Cannistrà, Melisa Diaz Lema, Chiara Masci, Anna Mergoni, Lidia Rossi and Mara Soncin ()
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Marta Cannistrà: Department of Management, Economics and Industrial Engineering, Politecnico di Milano, 20133 Milan, Italy
Melisa Diaz Lema: Department of Management, Economics and Industrial Engineering, Politecnico di Milano, 20133 Milan, Italy
Chiara Masci: Department of Mathematical Engineering, Politecnico di Milano, 20133 Milan, Italy
Anna Mergoni: Faculty of Economics and Business, KU Leuven, 3000 Leuven, Belgium
Lidia Rossi: Department of Management, Economics and Industrial Engineering, Politecnico di Milano, 20133 Milan, Italy
Mara Soncin: Department of Management, Economics and Industrial Engineering, Politecnico di Milano, 20133 Milan, Italy

Economies, 2023, vol. 11, issue 2, 1-20

Abstract: This paper investigates the determinants of mathematics performance by gender, exploiting a multilevel random forest approach. OECD PISA 2018 data from 28 European countries are employed to explore the performance of male and female students as a function of students’ family characteristics, their attitudes towards education, and class and school environment. Results show that the gender gap in favour of boys persists in most European countries. However, teacher and school practices like fostering student reading and creating a cooperative environment allow mitigating the influence of family background in countries without gender gap. Policy implications to foster performance equality are provided.

Keywords: mathematics achievement; comparative analysis; gender gap; random forest (search for similar items in EconPapers)
JEL-codes: E F I J O Q (search for similar items in EconPapers)
Date: 2023
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