Özet:

The purpose of this study is to explore to what extent PISA scores are predicted by the educational investments of countries which are available in OECD reports. Accordingly, teaching time, teacher salary, annual expenditure on educational institutions per student (AEPS), number of students per teaching staff (SPTS), and estimated class size were set as independent variables while PISA scores of countries (mathematics, reading, and science scores) were accepted as dependent variables. The data obtained from the reports prepared for a total of 26 out of around 40 OECD member countries (i.e. PISA scores of the countries in 2006, 2009, and 2012) were analyzed. Linear regression method was employed to predict the related PISA scores. Findings of the study indicated that teacher salary is a common variable that statistically influences predict students’ achievement in mathematics, reading, and science. Class size has revealed another variable that has a significant impact on predicting their achievement in mathematics and reading. All in all, teacher salary has proved a positive impact on students’ performance in mathematics, reading, and science while class size negatively influences their performance in mathematics and reading.