Situación espacio-temporal (Situation) 37 del acto judicial

Over the years, there has been much debate among educationalists and economists about the effects of class size on educational performance. This debate looks set to continue, and the issue remains topical in educational reform discussions. The issue on educational inputs variables more specifically of the class size; it needs to be considered in the context of a much wider debate on school funding and who should make decisions on how education is delivered.

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Examples of empirical studies with a focuses on class size in the recent past include: Glewwe et al (2004); Woessman (2003); Glewwe et al (2001); Krueger (1999), Case and Deaton (1999) and card and Krueger (1996). The main focus for most of the above studies is on the effect of class size (as a measure of school quality) on learning outcomes.

Card and Krueger (1996) summarized the results of twenty four estimates of the effect of school inputs; an OLS regression model was employed to investigate the association between the school expenditures on learning from eleven different studies. The research concluded that, all the estimate on subsequent learning, graduation rates, and years of education attainment have positive correlation. Furthermore, higher test scores do not indicate getting the well paid job and also of student's success in the labour market. It found that, there was a significant relationship between the quality of educational inputs and learning in developed countries.

Similarly in the US, Krueger (1997) used school level data with an experimental methodology. The Tennessee Student/Teacher Achievement Ratio (STAR) longitudinal study comprised 11,000 students, and their teachers from 80 schools which were randomly assigned to one of three types of classes: small classes (13- 17 student), regular-size classes (22-25), and regular-size aide classes (22-25) which included a full-time teacher’s aide.

The results showed that the students in small classes scored higher on standardised tests than students in regular sized classes but the findings varied across schools and student characteristics. The results indicated that the provision of a full time teacher support worker had a modest effect on student achievement. The main conclusions were that average performance on standardized tests increased by four percentile points the first year students attended small classes; the test score advantage of students in smaller classes expanded by about one percentile point per year in subsequent years; teacher aides and measured teacher characteristics had little effect and class-size had a larger effect for minority students and those having free school meals.

Overall, the study revealed significant effects of class-size on the test scores of young children (grade K-3). There were marked effects of school quality, as

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measured by Pupil Teacher Ratios (PTRs), on outcomes particularly for black children. There was a strong and significant effect of PTRs on enrolment, and educational performance more specifically on test scores for numeracy.

Using school-level data for 9 and 13 year olds from the Third International Mathematics and Science Study (TIMSS) Hanushek and Luque (2003), studied the relationship between classroom average scores and a number of school and non- school factors in individual countries. Their regression results demonstrated that class-size; educational qualifications of teachers, and teacher training within the classroom had statistically insignificant relationships with classroom scores in maths in the majority of the OECD countries. Their major finding regarding developing countries in particular was that there was little support for the ‘conventional view that school resources are relatively more important in less developed countries’. Hanushek (2003) argued that there is no strong or consistent relationship between the level of school inputs (teacher pupil ratio, spending per pupil, teacher education, experience and pay) and student performance, principally measured by student test scores.

In summary, the evidence from developed countries using the education production function claims that there is no clear, systematic relationship between school resources and student performance. However, recent research into the determinants of student performance strongly indicates that teacher input for example teacher quality makes a difference and is the most significant part of difference between schools (Hanushek, 2010).

Developing countries

Studies focusing on developing countries suggest that school infrastructure is an important factor for improved learning outcomes. Parental education and parental preferences for their children have also been the focus of research on student performance with the consensus being that more educated parents are likely to send their children to higher quality schools (Case and Deaton,1999; and Glewwe and Jacoby,1994). Parental income has also been shown to influence student performance with children from well to do families having higher scores (Hanushek 2003).

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Due to the problems of measuring the numerous inputs into the education process, experimental studies that control for unobserved heterogeneity (e.g. innate ability, motivation, and learning effort), have been used to study the impact of school resources on learning outcomes (Glewwe et al., 2004; Duflo, 2004; Angrist et al., 2002; Hoxby, 2000; Angrist and Lavy, 1999). For example, in a study investigating the effects of flip charts on test score performance in Kenya Glewwe et al., (2004) found conflicting results when retrospective or randomized experimental methods were utilised.

In developing countries, Deaton and Case (1999), examined the relationship between educational inputs especially Pupil-Teacher Ratio (PTR) and school outcomes such as enrolment, grade attainment and achievement in South Africa immediately before the end of the apartheid government. Educational resources were sharply different by race, with PTRs in Black schools more than twice as high as those in White schools. This study estimated regression equations on educational attainment (by age and race) and enrolment (by age, race - black, coloured white and Asian schools) and achievement on literacy and numeracy scores (black and white).

The findings discussed above differed sharply from what was often thought to be a consensus that school resources did not matter very much. The allocations resulted in marked disparities in average class-sizes, controlling for household background variables. Deaton and Case found a strong and significant effect of PTRs on enrolment, educational attainment and achievement confined to Blacks, consistent with the view that, reductions in class-sizes that characterize education for the other racial groups had little effect.

The limitation and critiques on education production function highlighted by Card and Krueger (1996) show that test scores are inappropriate as an outcome measure, as their explanatory power is very limited, and in some circumstances that test scores do not adequately reflect school outputs. They suggest that the level of educational attainment and earnings have to be used as key outcome measures. They found a positive and statistically significant association between education resources (expenditure per pupil and pupil-teacher ratio), and educational attainment and earnings.

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Wobmann (2000; 2001) also analyzed the determinants of student performance using the TIMSS data set. Despite the fact that these findings are not specific to developing countries, the general conclusion was that differences in student performance cannot be explained by differences in school resources. However, these results did reveal that the institutional features of a nation’s education system had a notable impact on student outcomes.

Using school level data for 9 and 13 year aged children using the TIMSS dataset, Hanushek and Luque (2003) looked at the relationship between classroom average scores and a number of school and non-school factors in individual countries. The regression results revealed that student teacher ratio, teacher qualification, and teacher having had training had statistically insignificant relationships with classroom scores in maths in the majority of the countries.

The TIMMS study tested representative samples of students aged 13 years in 38 countries and estimated the effect of class-size on student performance in 11 countries. The education production function was estimated and using a least square regression the degree of relationship between inputs and outcomes was established. The results demonstrated that the effect of class-size on student performance was not large; however, the results for individual countries were much more diverse. Furthermore, smaller class-size had a better effect on student achievement only in countries where the average capability of the teaching force appeared to be low (Wobmann and West, 2006).

Over the years, there has been much debate among educationalists and economists about the effect of class size on educational performance. The debate looks set to continue, and the issue remains topical in educational reform discussions. The issue of class size needs to be considered in the context of a much wider debate on school funding and who should make decisions about how education is delivered. Factors such as the length of the school year and day, the numbers of classes teachers have, and the proportion of time teachers spend teaching may all contribute to the difference. Although, many people argue that smaller class sizes are both a necessary and sufficient means of achieving improved educational outcomes, there is a wide literature on other determinants of

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educational quality. In comparing the evidence, it is difficult to draw firm conclusions, due to differences in methodology and the definitions used.