In the educational context, one of the main goals is to reduce the disparities among students, generally at the national level, to allow all individuals to achieve a similar cultural background. Using data from a large-scale standardised test administered by INVALSI (National Institute for the Evaluation of the Educational System), this paper offers a first longitudinal analysis of the performance in the maths test of a cohort of students enrolled in 2013/2014 at grade 8 and observed up to grade 13. The aim is to identify those obstacles that undermine students’ learning to help them adopt informed educational actions. Specific features of these data are their hierarchical structure and the presence of not vertically scaled scores. Two approaches have been followed for their analysis: growth models and growth percentiles. Coherently with the literature, our results suggest the presence of a gender gap and a significant impact on the type of school and social-cultural background. Unlike previous research on the INVALSI data, we evaluate these time-invariant covariates’ effects on students’ performance over different school cycles.

Assessing maths learning gaps using Italian longitudinal data / Bianconcini Silvia; Mignani Stefania; Mingozzi Jacopo. - In: STATISTICAL METHODS & APPLICATIONS. - ISSN 1618-2510. - STAMPA. - 32:3 (September)(2023), pp. 911-930. [10.1007/s10260-022-00676-9]

Assessing maths learning gaps using Italian longitudinal data

Bianconcini Silvia
Primo
Membro del Collaboration Group
;
Mignani Stefania
Secondo
Membro del Collaboration Group
;
2023

Abstract

In the educational context, one of the main goals is to reduce the disparities among students, generally at the national level, to allow all individuals to achieve a similar cultural background. Using data from a large-scale standardised test administered by INVALSI (National Institute for the Evaluation of the Educational System), this paper offers a first longitudinal analysis of the performance in the maths test of a cohort of students enrolled in 2013/2014 at grade 8 and observed up to grade 13. The aim is to identify those obstacles that undermine students’ learning to help them adopt informed educational actions. Specific features of these data are their hierarchical structure and the presence of not vertically scaled scores. Two approaches have been followed for their analysis: growth models and growth percentiles. Coherently with the literature, our results suggest the presence of a gender gap and a significant impact on the type of school and social-cultural background. Unlike previous research on the INVALSI data, we evaluate these time-invariant covariates’ effects on students’ performance over different school cycles.
2023
Assessing maths learning gaps using Italian longitudinal data / Bianconcini Silvia; Mignani Stefania; Mingozzi Jacopo. - In: STATISTICAL METHODS & APPLICATIONS. - ISSN 1618-2510. - STAMPA. - 32:3 (September)(2023), pp. 911-930. [10.1007/s10260-022-00676-9]
Bianconcini Silvia; Mignani Stefania; Mingozzi Jacopo
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/907314
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