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Abstract
This article investigates the effect of change in average age, socio‐economic status (SES) and class size upon the change in average reading achievement between the Progress in International Reading Literacy Study (PIRLS) 2001 and PIRLS 2006 at the country level. First, we consider the effect of age upon reading achievement. We use regression–discontinuity to analyze the effects of age and schooling upon reading achievement. A tentative correction for age differences yields a new ranking of countries with regard to their corrected average achievement in PIRLS 2006. Second, in order to facilitate cross‐country comparisons in respect of educational equity, we construct internationally acceptable SES indices for PIRLS 2001 and PIRLS 2006. Third, we investigate the effects of change in class size, age and SES upon the change in reading achievement through regressions. We find that the change in reading achievement at the country level can be partially explained by the change in age but not by the change in SES or class size.
Acknowledgements
We are grateful to the European Science Foundation, who sponsors our ESF‐ECRP project, ‘Establishing a Knowledge‐base for Quality in Education’. Special thanks are due to Georges Van Landeghem, Xavier Dumay, Nkafu D. Anumendem and the anonymous reviewers for their helpful comments.
Notes
1. The variable name as mentioned in the codebooks is ASBHBOOK.
2. The variable name as mentioned in the codebooks is ASBHCHBK.
3. The variable name as mentioned in the codebooks is ASBHWELL.
4. The variable name as mentioned in the codebooks is ASDHPEMP.
5. The variable name as mentioned in the codebooks is ASDHEDUP.
6. The variable name as mentioned in the codebooks is ASDHOCCP.
7. The variable name as mentioned in the codebooks is ASBGTA1.
8. The variable name as mentioned in the codebooks is ASBGTA2.
9. The variable name as mentioned in the codebooks is ASBGTA3.
10. The variable name as mentioned in the codebooks is ASBGTA4.
11. The variable name as mentioned in the codebooks is ASBGTA5.
12. The variable name as mentioned in the codebooks is ASBGTA6.
13. The variables with name ASBGTA7, ASBGTA8, ASBGTA9 and ASBGTA10.
14. The senate weight is a type of sampling weight used in the IEA international student survey. These sampling weights can be used when international estimates are sought and you want to have each country contribute the same amount to the international estimate. When this variable is used as the sampling weight for international estimates, the contribution of each country is the same, regardless of the size of the population.
15. Coded: 1, 0–10; 2, 11–25; 3, 26–100; 4, 101–200; 5, > 200.
16. Ranging from 1 to 4 according to the amount of educational aids that are at the child’s disposal at home.
17. Coded: 1, never worked outside home for pay; 2, general worker; 3, skilled worker; 4, clerical; 5, small business owner; 6, professional.
18. Coded: 1, some primary, lower‐secondary or no schooling; 2, finished lower‐secondary education; 3, finished upper‐secondary education; 4, finished post‐secondary, but not university; 5, finished university or higher.
19. In the PCA the four SES variables were considered to be continuous variables. The number of ‘educational aids’ is obvious. For the other three variables, it is acceptable because there are five or more response categories which are ordered. The only category in which this is not the case, is the one ‘occupation not applicable’ of the variable ‘highest occupation level of the parents’; that is a rest category, which is small (< 6% in 33 of the 42 countries, < 11% in 40 of the 42 countries). After including this category as a separate dummy variable, the factor loading was low; for that reason the variable was excluded from the model.
