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The Long March Towards School and Student Assessment in Italy

  • Rosalia Castellano
  • Sergio LongobardiEmail author
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Abstract

The assessment culture has had considerable difficulty in permeating the Italian school system, and the themes of school evaluation have entered the Italian political agenda only in the last 15 years, although the Italian participation in international student assessments such as PISA, TIMSS and PIRSL has always been significant. A common denominator of the results obtained by these international surveys concerns the fairness, in territorial terms, of the Italian school system. A deeper analysis of IEA and OECD data, confirmed also by the Italian National System of Evaluation (SNV), emphasizes the presence of a skill gap between students from central-northern regions (more developed) and those from southern regions (less developed). The literacy divide is the real challenge for Italian policy makers, but its solution seems to be very far, although in the last years, an ambitious set of reforms regarding the educational system (The Good School Act, Law 107/15) and the labour market (The Industry 4.0 National Plan and Jobs Act) has been launched. These policies aimed to improve the competences of Italian students and to strengthen the linkages between the education system and the world of work, but their results will only be assessed in the long term.

References

  1. Agasisti, T., & Vittadini, G. (2012). Regional economic disparities as determinants of students’ achievement in Italy. Research in Applied Economics, 4(1), 33–54.Google Scholar
  2. Ballarino, G., & Panichella, N. (2016). Social stratification, secondary school tracking and university enrollment in Italy. Contemporary Social Science, 11(2–3), 169–182.CrossRefGoogle Scholar
  3. Bertoni, M., Brunello, G., & Rocco, L. (2013). When the cat is near the mice won’t play: The effect of external examiners in Italian schools. Journal of Public Economics, 104, 65–77.CrossRefGoogle Scholar
  4. Bratti, M., Checchi, D., & Filippin, A. (2007). Geographical differences in Italian students’ mathematical competencies: Evidence from PISA 2003. Giornale degli Economisti e Annali di Economia, 66(3), 299–333.Google Scholar
  5. Breakspear, S. (2012). The policy impact of PISA: An exploration of the normative effects of international benchmarking in school system performance (OECD Education Working Papers, No. 71). Paris: OECD Publishing.  https://doi.org/10.1787/5k9fdfqffr28-en.
  6. Damiani, V. (2016). Large-scale assessments and educational policies in Italy. Research Papers in Education, 31(5), 529–541.  https://doi.org/10.1080/02671522.2016.1225354.CrossRefGoogle Scholar
  7. Longobardi, S., Falzetti, P., & Pagliuca, M. M. (2018). Quis custiodet ipsos custodes? How to detect and correct teacher cheating in Italian student data. Statistical Methods and Applications, 27, 515–543.  https://doi.org/10.1007/s10260-018-0426-2.CrossRefGoogle Scholar
  8. Montanaro, P. (2008). Territorial differences of Italian students’ achievement: Evidence from national and international assessments (Bank of Italy Occasional Paper No. 14/08). Rome.Google Scholar
  9. Organisation for Economic Cooperation and Development. (2009). PISA data analysis manual: SPSS and SAS (2nd ed.). Paris: OECD.Google Scholar
  10. Organisation for Economic Cooperation and Development. (2017). Getting skills right: Italy, getting skills right. Paris: OECD Publishing.  https://doi.org/10.1787/9789264278639-en.CrossRefGoogle Scholar
  11. Organisation for Economic Cooperation and Development. (2018). OECD skills strategy diagnostic report: Italy 2017, OECD skills studies. Paris: OECD Publishing.  https://doi.org/10.1787/9789264298644-en.CrossRefGoogle Scholar
  12. Paccagnella, M., & Sestito, P. (2014). School cheating and social capital. Education Economics, 22(4), 367–388.  https://doi.org/10.1080/09645292.2014.904277.CrossRefGoogle Scholar
  13. Quintano, C., Castellano, R., & Longobardi, S. (2009). A fuzzy clustering approach to improve the accuracy of Italian student data. Statistica & Applicazioni, 7(2), 149–171.Google Scholar
  14. Quintano, C., Castellano, R., & Longobardi, S. (2012). The effects of socioeconomic background and test-taking motivation on Italian students’ achievement. In A. Di Ciaccio, M. Coli, & J. M. A. Ibañez (Eds.), Advanced statistical methods for the analysis of large data-sets (pp. 1–484). Berlin: Springer.Google Scholar

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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.University of Naples “Parthenope”NaplesItaly

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