Teacher Education and Development Study in Mathematics - IEA

PART 1: INTRODUCTION
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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