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User:Raeganrust/Educational inequality

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Measurement[edit]

In the last decade, various tests have been administered throughout the world to gather information about students, the schools they attend, and their educational achievements. These tests include the Organization for Economic and Co-Operational Development's Program of International Student Assessment and the International Association for the Evaluation of Educational Achievement's Trends in International Mathematics and Science Study. To calculate the different test parameters in each country and calculate a standard score, the scores of these tests are put through Item Response Theory models. Once standardized, analysts can begin looking at education through the lens of achievement rather than looking at attainment. Through looking at achievement, the analysts can objectively examine educational inequality throughout the globe.

Besides the use of achievement, analysts are able to use a few other methods, including but not exclusive to the Living Standard Measurement Study and the Index of Regional Education Advantage. China implemented the IREA to better understand regional differences from East to West in their country over a period of three years while Albania took a look at individual households to better understand their education differences.

Albania Educational Inequality Study

In an effort to better understand home welfare The World Bank Organization has created a Living Standard Measurement Study program that helps analyze poverty in developing countries and allows for utilization in various empirical analysis studies. A study done by Nathalie Picard and Francois Wolff in Albania utilized the LSMS framework to further their study into educational inequalities within Albania. With the data presented from the LSMS models, Picard and Wolff were able to use empirical methods to determine that nearly 40% of educational differences in the country were due to household differences between families.The LSMS framework is composed of household and individual well being questions that assess the welfare state of the house. Data for various regions can be viewed on their public website. Within the survey are questions related to educational background that help the analytics team better relate the household state and region to the existing education levels. Through the Albania study, Picard and Wolff were able to utilize these statistics to help illustrate the educational levels between various households and different income levels in Albania. This practice can be implemented in many locations worldwide.

China Regional Educational Inequality Study

China incorporated an index called the Index of Regional Education Advantage or IREA to help analyze the effects that new policies had on their countries education system throughout their various regions. This multidimensional index includes a higher comprehensive list of dimensions than the Gini index in relation to education and therefore brings a greater understanding of the disparities in education. Founding off three core values of provision, enrollment, and attainment within the education system the IREA index is able to utilize conversion factors to create a capability set to diagnose the education levels of their different regions. Since all three are not independent variables it is critical to utilize items like geometric means when calculating values like enrollment and attainment. Due to the IREA being a composite summary index it is common to utilize weighted indicators to show importance of each core value . When evaluating the finalized scores of the regions China produced spatial pattern diagrams with data over three years to reflect any changes over the associated time period. The scores give a visual of the regional inequalities in their education. A change to a darker color indicated that the education had worsened in score. This comprehensive IREA score reflects the true condition of the area in question.