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Regional Economic Disparities as Determinants of Students’ Achievement in Italy: Factors

Regional Economic Disparities as Determinants of Students’ Achievement in Italy: FactorsHowever, their main result is that factors affecting students’ achievements are related to (i) the socio-economic status (SES), (ii) the macro-area of the country (Northern Italy schools perform much better than their Central, Southern and Isles counterparts), and (ii) the type of school (academic schools – Licei – and technical schools perform better than vocational schools). Another interesting result is that private schools perform worse than public ones (this result is consistent also with the international comparison proposed by Vandenberghe & Robin, 2004, and with previous work of the authors themselves, e.g. Bertola & Checchi, 2004). Nevertheless, Vittadini challenged this specific result. The author argued that there were methodological problem in the analysis, as he raised doubts on (i) the validity of using OECD-PISA data for a public/private schools comparison in Italy (because of the particular sampling strategy of OECD-PISA) and (ii) on the use of cross-sectional data. Emotional Intelligence

Another study in this field is that of Longobardi et al.. They employ a multilevel modelling to analyse the effects of different covariates on students’ performances, by using OECD-PISA2006 data (their study, too, was conducted with students as the units of observation). Their statistical analysis (that is more robust than previous ones as it explicitly accounts for the hierarchical nature of data) pointed out results, which are consistent with Bratti et al. : (i) a gap between Northern and Southern part of Italy, (ii) strong differences among schools’ types (namely, with Licei schools outperforming technical and vocational schools), (iii) a major impact of socio-economic background in predicting students’ results. Through their results, the authors concluded that even a high-centralized system as the Italian was not actually able to guarantee homogenous students’ performances.
Agasisti also contributed to the debate with two papers. Both contributions rely upon OECD-PISA2006 data, but they differ with regard to the methodological approach: the first specifies an Educational Production Function through multivariate regressions, while the second realises a Data Envelopment Analysis. In both cases, data are aggregated at school-level. The results are pretty similar to those provided by the papers previously cited, and more specifically they evidenced: the role of geographical gaps, the type of school, the socio-economic conditions of students. Moreover, in both articles a measure of competition has been added among the explanatory set of covariates, to investigate whether competition actually fosters schools’ performance (the empirical results partially confirm this hypothesis); Ponzo also confirms this latter finding.
The main objective of this paper is to describe the main determinants of the students’ achievement (as measured by the Invalsi test) in Mathematics, with reference to the year 2008/09. While focusing on this objective, the paper also deals with two factors traditionally considered as very important for explaining Italian schools’ results: (i) the geographical location and (ii) the average socio-economic status (SES) of students attending the schools. The former factor derives from the evidence that schools in Northern Italy outperform those in Southern Italy; moreover, previous literature about other countries demonstrated the heterogeneity in educational production across different areas within countries (i.e. differences among Regions). The potential role of SES is related to the lower performances associated to schools with higher proportion of students from disadvantaged families.
The paper is organised as follows. The next section contains a detailed presentation of data and methodology. The third section presents the results; the fourth discusses the main implications, illustrates the methodological suggestions derived from the empirical analyses (while providing a potential further agenda), and concludes.

This post was written by , posted on January 1, 2014 Wednesday at 12:05 pm