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; Mara Soncin (Economies, 2023)
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: 330; comparative analysis; gender gap; mathematics achievement; random forest