Teacher Education and Development Study in Mathematics - IEA

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PART 1: INTRODUCTION 19 Many studies have attempted to explain why students in some countries achieve higher scores on international tests. Many of these studies focus on differences in performance between students of higher and students of lower socioeconomic status (SES) (see, for example, Willms, 2003); others include proxies for teacher quality, usually teacher education, experience, and measures of teacher attitudes (see, for example, Carnoy, Marshall, & Socias, 2003; OECD, 2004b). Some consider opportunity to learn (Carnoy et al., 2003; Schmidt et al., 2002), and some investigate the varying social contexts of schooling in different countries (Carnoy, Gove, & Marshall, 2007). However, these studies and those done within countries using student performance as an outcome find it difficult to identify the teacher characteristics that contribute to higher student performance. The main reason why seems to be that these teacher characteristics are either not well identified or relate strongly to student SES (bettereducated teachers are likely to be teaching in schools containing students primarily from higher SES backgrounds, for example). Our study focuses on a variable that has not traditionally been part of the analyses of student performance across countries, namely teacher relative salary as a proxy for teacher quality. This variable may correlate with others related to student performance, such as opportunity to learn, as measured by the mathematics curriculum (Schmidt et al., 2002). Societies that recruit more academically able mathematics teachers may also be able to require a more demanding mathematics curriculum. We do not have measures of opportunity to learn for all the countries in our sample, but we are aware that teacher relative salary and opportunity to learn might be highly correlated factors that contribute to student achievement. Income inequality in a society might also figure into relative teacher pay and higher student achievement: the greater the income inequality in a post-industrial society, especially in today’s technology-oriented global economy, the more likely it is that those with relatively good mathematics skills will receive higher levels of pay than those without such skills. Yet, there are societies that “regulate” income inequality more than others do. Canada, for example, has about the same level of technology use and science-based industries as the United States, but Canada’s income distribution is more equal (Deininger & Squire, 1996). Societies have preferences for more or less income inequality, and this preference may influence differences in income between, say, teachers and those in mathematics-intensive professions. Income inequality in a society may therefore be one variable suggestive of the relative quality of mathematics teachers in that society. The higher the average level of mathematics skills in a society and the more equal the income distribution, the lower the expected cost of recruiting into teaching those with relatively scarce skills, such as high levels of proficiency in mathematics. Income, or gross domestic product (GDP) per capita, correlates highly with the average level of adult educational attainment, which means that educational attainment should reflect the degree of mathematics skill in the society. As such, we can use GDP per capita as a rough approximation of the level of mathematics skills in the society, and income distribution as a rough measure of the cost of recruiting individuals with high mathematics skills into teaching. Societies with greater income inequality may also be marked by more unequal distribution of teacher skills among students (Chiu & Khoo, 2005). Unequal income distribution may therefore not only influence the level of mathematics skills in the
20 TEACHER PAY AND STUDENT MATHEMATICS ACHIEVEMENT teacher labor force, but also the distribution of those skills across social class groups. In societies where income is more equally distributed, teachers with high mathematics skills may be less averse to teaching in schools containing students from lower social class levels than teachers in societies where income is more variable because the social distance between the lower and the higher social classes is smaller. Another possibility is that, in societies with more equal income distribution, classrooms vary less in terms of their teaching conditions than is the case in more unequal societies. Teachers of equal mathematics skills are thus more likely to be found across the spectrum of classrooms in the education system. And if we assume that higher teacher mathematics skills yield a higher payoff in classrooms with students from lower SES backgrounds, we can then also assume that countries with more equal distribution of teacher skills will have higher levels of average student mathematics performance. If teacher mathematics skills are, indeed, an important factor explaining student performance in mathematics, we should find relationships between student mathematics performance on international tests, such as TIMSS and PISA, and on measures of both GDP per capita (a proxy for the overall level of mathematics skills available in the labor market) and income distribution. We should also find that, assuming we control for GDP per capita and income distribution, students have higher levels of mathematics performance in nations where teacher wages are higher relative to the wages of workers in mathematics-intensive professions. We explore both these notions in the first part of this publication. We briefly summarize the results of our comparison across 20 countries of (estimated) teacher age/income profiles for various years with the age/income profiles of professionals in mathematicsintensive professions. When developing our estimates, we controlled for gender and level of education. We found that, in many of the 20 countries, salaries of teachers are similar to those of professionals in mathematics-intensive occupations. However, in the remaining countries, this is not the case. (The 20 country studies comprise the second part of this report.) We also, in the first section of the report, estimate the relationship between student mathematics test scores on the TIMSS and PISA mathematics tests, GDP per capita, income distribution, and teachers’ salaries relative to the salaries of people of the same gender with a similar level of education (usually completed university) who are employed or trained as scientists. We use country as the unit of observation. The results of this analysis suggest that student performance is positively and statistically significantly related to relative teacher salaries in the case of male (but not female) teachers, even when controlling for GDP per capita and income distribution. We discuss these results and how they might inform continued research on the effect that paying higher relative salaries to teachers potentially has on student mathematics performance. We need to caution that the results are essentially suggestive, not causal. As we point out in the conclusions, there are several possible reasons for the correlation between teachers’ relative pay and higher student performance, only one of which is that higher teacher pay draws individuals with higher mathematics skills into teaching, thereby resulting in better student performance.
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Teacher Education and Development Study in Mathematics - IEA

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