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2014 | OriginalPaper | Chapter

A Value Added Approach in Upper Secondary Schools of Lombardy by OECD-PISA 2009 Data

Authors : Isabella Romeo, Brunella Fiore

Published in: Analysis and Modeling of Complex Data in Behavioral and Social Sciences

Publisher: Springer International Publishing

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Abstract

In the last decade a great deal of interest at the national and international level has been shown in measuring the school impact on student achievement. Standardized tests and the Value Added Methodology have emerged as the appropriate instruments for this purpose. The aim of this paper is to find a value added measure for upper secondary schools of the Lombardy region from the OECD-PISA 2009 data. The initial cognitive level of the student, which is necessary for the analysis, has been obtained by summarizing different teachers’ evaluations from a Rasch analysis. A multilevel model has been fitted to control the student and school factors effecting the reading results. In particular, even the reading enjoyment variable has been considered, since it explains a high variability of student performance. The ranking of the upper secondary schools based on the value added measures is compared with the one obtained using raw data, showing significantly different results.

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Footnotes
1
PISA 2012 data are not available yet.
 
2
The PVs are meant to prevent biased inferences, which can occur as a result of measuring the not directly observable student skill. Instead of directly estimating it, a probability distribution is estimated. Then the PVs are random draws from this distribution. The required statistic and its respective standard error have to be computed for each plausible value and then put together (PISA 2012).
 
3
Given the PISA complex sample design, the use of replicates is needed to obtain reliable sampling variances. The Fay’s variant of the Balanced Repeated Replication (BRR) is used (PISA 2012).
 
4
This variable (JOYREAD index) is derived by OECD, putting together eleven items (PISA 2012) by a scaling procedure (Item Response Theory).
 
5
This variable was created by OECD on the basis of the occupational and educational level of the student’s parents, home educational and cultural resources (PISA 2012).
 
6
The variable assumes value one if the school is located in a town with fewer than 100,000 people otherwise it assumes value zero.
 
7
In Italy there are many types of liceo: classical, scientific, socio-pedagogical.
 
Literature
Bond, T. G., & Fox, C. M. (2001). Applying the Rasch model: Fundamental measurement in the human sciences. London: Lawrence Erlbaum Associates Publishers.
Brozo, W. G., Shiel, G., & Topping, K. (2001). Engagement in reading: Lessons learned from three PISA countries. Journal of Adolescent & Adult Literacy 51, 304–314.CrossRef
Ferrao, M. E., & Goldestain, H. (2009). Adjusting for measurement error in the value added model: Evidence from Portual. Qualitative and Quantitative, 43, 951–963.CrossRef
Goldstein, H., Huiqi, P., Rath, T., & Hill, N. (2000). The use of value added information in judging school performance. London: Institute of Education.
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Timmermans, A. C., Doolaard, S., & De Wolf, I. (2011). Conceptual and empirical differences among various value-added models for accountability. School Effectiveness and School Improvement, 22, 393–413.CrossRef
Wang, J. H. Y., & Guthrie, J. T. (2004). Modeling the effects of intrinsic motivation extrinsic motivation, amount of reading, and past reading achievement on text comprehension between U.S. and Chinese student. Reading Research Quarterly, 39, 162–186.
Metadata
Title
A Value Added Approach in Upper Secondary Schools of Lombardy by OECD-PISA 2009 Data
Authors
Isabella Romeo
Brunella Fiore
Copyright Year
2014
Book
Analysis and Modeling of Complex Data in Behavioral and Social Sciences

Print ISBN: 978-3-319-06691-2

Electronic ISBN: 978-3-319-06692-9

Copyright Year: 2014

DOI
https://doi.org/10.1007/978-3-319-06692-9_26

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