A SET OF INDICATORS FOR POLICY IN THE EDUCATION FIELD
INVALSI (ITALY)
About this paper:
Conference name: 17th annual International Conference of Education, Research and Innovation
Dates: 11-13 November, 2024
Location: Seville, Spain
Abstract:
Goals:
The research objective is to describe the indicators that can be provided to policy makers of the education system in order to make decisions to improve the educational level of the school population.
The indicators, based on INVALSI data (national institute for the evaluation of the educational and training system), disaggregated territorially and by population subgroups, are useful for identifying areas of intervention and directing specific resource investments by the government.
Description:
Different types of indicators will be presented:
a) academic performances for self-evaluation and improvement of each school;
b) score variability between classes and schools as a proxy of equity;
c) students' socio-economic-cultural background (ESCS);
d) “hidden” dropout.
Results:
a) INVALSI computes an academic performance for each student in the 4 subjects of its standardized tests, built on what they should know at the end of each school cycle; then process these scores in order to define a “competence level” of each student; at the end of the process returns every year personal performance to each student along with several data to all the schools where the (Italian, Math and English) tests are administered: they are provided in tables and graphs, aggregated by class/school and compared to different benchmarks according to the territory, the socio-economic context or the school type.
b) In an ideal school, the variability of student scores at INVALSI tests is maximized inside the single classes and minimized between the classes, so that classes have similar score average but more heterogeneity inside; in an ideal territory, the variability of average scores at INVALSI tests is maximized inside the single school and minimized between schools: INVALSI proposes that variability as a measure of equity in a region for example, or as a measure of balanced composition of classes.
c) Along with the standardized tests, INVALSI collects other data to estimate the student’s and the school socio-economic context; the ESCS index is inspired by international similar indexes and is based on a synthesis of 3 indicators: parents’ occupational status, parents’ education level, students’ possession of some specific tangible assets. It gives also the possibility to schools to compare their average performances to those obtained by schools with a similar context.
d) Since few years, INVALSI data are used to compute the number of ILET (Implicit Leavers from Education and Training), that is those students which achievement level is insufficient in all the subjects examined by INVALSI tests in grade 8 or 13 (Italian, Maths, English both reading and listening). These students obtain the «diploma» but they don’t reach level 3 in Italian language and Mathematics and don’t even reach level B1 in English listening and reading; their levels match the learning goals required for low secondary schools students, that is definitely lower than expected. This could be a proper group of students to be chosen for improvement projects.
References:
[1] https://www.invalsi.it/download/wp/wp02_Ricci.pdf
[2] https://www.invalsiopen.it/wp-content/uploads/2019/10/Editoriale1_ladispersionescolasticaimplicita.pdf
[3] https://serviziostatistico.invalsi.it/wp-content/uploads/2023/04/ricerca-11_giangiacomo.pdfKeywords:
Learning, learning equity, learning achievement, data literacy, implicit dropout.