318 research outputs found
School size and students' achievement. Empirical evidences from PISA survey data
No full textThe issue of school size has become prominent for researchers and policy makers alike. Many different arguments have been offered in order to explain how school size might affect student achievement. Overall, if smaller schools are associated with higher students' achievement in primary level, this conclusion cannot be clearly stated for the secondary schools. Empirical evidences highlight that the effect is often mixed: some studies have found higher achievement among students enrolled in smaller schools, while others have detected higher achievement in very large schools, still others have suggested a non linear relationship. In this paper, analyzing OECD-PISA 2012 data, the effect of school size is investigated considering Italian students' achievement, in order to answer the question if there is an optimal school size in Italy. For our goal, due to the hierarchical structure of data (the students are nested within school) we specify a mixed model with random intercept
Student background determinants of reading achievement in Italy. A quantile regression analysis
No full textIn recent years determinants of students’ achievement has received much attention. Empirical studies
have found that students’ characteristics, family background, school attended, and regional residence are
major factors affecting student performance. In this paper, we analyze the 2009 OECD-PISA (spell PISA)
survey to examine individual background characteristics influencing the reading achievement of Italian
15 years-old students using the quantile regression (QR) approach. The QR approach allows researchers
to analyze changes in size and direction of predictor estimates on student performance across the entire
distribution of reading achievement scores. Results indicate significant effects of predictors on reading
achievement operating differently across quantiles, suggesting different pathways to achievement for
low and high performing readers. In particular, some family background predictors (parental education,
computer availability at home, and availability of a desk for homework at home), the school program
attended and, the region of student residence play important but differing role for low and high
performing readers. For example, parental education shows a positive effect on student reading,
academic (general) programs perform better than vocational or technical, and Northern regions perform
better than Center-Southern ones, with differentiated effects along the distribution of students’ reading
scores. These findings should be carefully considered by policymakers when outlining strategies to
enhance student performance at all levels along the reading continuum of low and high scores
Introduction to Latent Class Analysis With Applications
No full textLatent class analysis (LCA) is a statistical method used to group individuals (cases, units) into classes (categories) of an unobserved (latent) variable on the basis of the responses made on a set of nominal, ordinal, or continuous observed variables. In this article, we introduce LCA in order to demonstrate its usefulness to early adolescence researchers. We provide an application of LCA to empirical data collected from a national survey carried out in 2010 in Italy to assess mathematics and reading skills of fifth-grade primary school pupils (10 years in age). The data were used to measure pupils’ supplies of cultural capital by specifying a latent class model. This article aims to describe and interpret results of LCA, allowing users to replicate the analysis. All LCA examples included in the text are illustrated using the Latent GOLD package, and command files needed to reproduce all analyses with SAS and R are available as supplemental online appendix files along with the example data files
Matematica, escapismo e detenzione
No full textIn questo lavoro si esaminano i legami tra escapismo, regime di detenzione e produzione scientifica matematica: come l'astrazione ha spesso tratto beneficio da periodi di isolamento sociale, volontario e non
I restauri misti: valutazione allo stereomicroscopio e al SEM di differenti tecniche operative.
No full textsj-pdf-1-vdi-10.1177_10406387211043513 – Supplemental material for Measurement of progesterone in sheep using a commercial ELISA kit for human plasma
No full textSupplemental material, sj-pdf-1-vdi-10.1177_10406387211043513 for Measurement of progesterone in sheep using a commercial ELISA kit for human plasma by Valeria Pasciu, Maria Nieddu, Elena Baralla, Cristian Porcu, Francesca Sotgiu and Fiammetta Berlinguer in Journal of Veterinary Diagnostic Investigation</p
Students mobility: assessing the determinants of attractiveness across competing territorial area
No full textA central question for education authorities has become ‘‘which factors make a
territory attractive for tertiary students?’’ Tertiary education is recognised as one of the
most important assets for the development of a territory, thus students’ mobility becomes a
brain drain issue whenever there are prevalent areas that attract students from other territories.
In this paper, we try to identify the most important factors that could affect student
mobility in Italy. In doing that we analyse students’ flows across competing territorial areas
which supply tertiary education programs. We will consider a wide range of determinants
related to the socio-economic characteristics of the areas as well as resources of the
universities in the territories in terms of variety and quantity of the degree programs there
available, financial endowments provided by Central Government, and services available
to students. The Bradley–Terry modelling approach based on pair comparisons has been
adopted to define the attractiveness of competing territories and assess how much the
detected divergences can be attributed to factors directly related to the considered characteristics
of the universities in the territory and how much is ascribable to inherent
characteristics of the areas where the universities are located such as the labour market
conditions. Furthermore, the adopted approach allows us to consider uncertainty in
defining territorial attractiveness and making comparisons. In this way, we would like to
provide some evidences to assess if the rules currently used by the Central Government to
finance public universities on the basis of their capabilities to attract students really reward
the efforts made by the university system in the area to improve their standard of quality or,
on the contrary, reward the territorial features
Adjusted indicators of quality and equity for monitoring the education systems over time. Insights on EU15 countries from PISA surveys
No full textIn this work, we investigate how European countries belonging to EU15 are performing in terms of the quality and equity of their educational systems. To do so, we jointly analysed student competencies in mathematics and reading using data collected in four different waves (2006, 2009, 2012, 2015) by the Program for International Student Assessment (PISA) run by the Organisation for Economic Cooperation and Development (OECD). The aim of this analysis is twofold: (i) to assess the associations between students' competencies inmathematics and reading and their socioeconomic status and to investigate how this relationship varies across countries over time; (ii) to present a batch of adjusted indicators relevant to the investigation of educational performance over time in terms of quality (average student competencies) and equity (low association between student achievement and their socioeconomic backgrounds). We fitted a mixed-effect (multilevel) regression model with a bivariate latent structure and random intercepts and slopes to assess the effect of socioeconomic and cultural background on student competencies across countries over time and to assess the performance trajectories of EU15 countries with respect to European Commission benchmarks. We present and discuss our main findings and their implications in terms of the policies of EU15 countries
Does education protect families' well-being in times of crisis? Measurement issues and empirical findings from IT-SILC data
No full textThis study analyses the relationship between education and material well-being from a longitudinal perspective using the European Survey on Income and Living Conditions (EU-SILC) data collected in Italy in four waves (2009-2012). It has two main aims: (i) to measure household material well-being on the basis of householders' responses to multiple survey items (addressed to gather information on the household availability of material resources) by advancing indexes, which can account for global and relative divergences in households' material well-being across survey waves; (ii) to assess how education and other sociodemographic characteristics affect absolute well-being and its variation (i.e. relative well-being) in the time span considered. Both aims are pursued, combining measuring and explanatory modelling approaches. That is, the use of the Multilevel Item Response Theory model allows to measure the global household material well-being and its yearly variation (i.e. relative material well-being) in the four waves. Meanwhile, the use of a multivariate (and multivariate multilevel) regression model allows to assess the effects of education and other sociodemographic characteristics on both components (absolute and relative well-being), controlling for the relevant sources of heterogeneity in the data. The value added to using the proposed methodologies with the main findings and economic implications are discussed
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