An Examination of International Drivers of Educational Achievement

In this paper I analyze the various factors that drive educational achievement across various countries using regression analysis. The causal model includes the variables which describe family background, learning resources, school characteristics, learning approaches, and class features to fully account for all of the features that contribute to educational achievement. The Programme for International Student Assessment (PISA) 2006 data is used to compare the individual factors in relation to the achievement scores in math and science through statistical regression analysis. The majority of the variables behave in a way that confirms the expected outcomes: characteristics such as having a history of education in the family or possession of the proper resources to be an effective student all have positive impacts on the PISA achievement scores in both subjects. This paper also analyzes the relationship of achievement in different countries relative to the U.S. and extracts the main drivers of education, which have the greatest impact on achievement scores relative to all of the variables included. I would like to thank my thesis adviser, Professor Grubb, for all of his guidance throughout the modeling and writing of my honors thesis.