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Disaggregation and mapping of PISA math scores by social class

Mon, April 15, 3:15 to 4:45pm, Hyatt Regency, Floor: Bay (Level 1), Bayview A/B Foyers

Proposal

When thinking of top global academic achievers, generally a few specific countries or regions come to mind. While rankings may vary year to year, there do exist undeniable global educational leaders. East Asia in particular, whose countries consistently hold the majority of top spots in in most educational ranking lists (Schneider and Lee 1990; Jerrim 2015). Often these countries or regions are held up as standards for educational excellence. However, rankings are made based on mean scores of students within a given country. This ignores the great diversity of backgrounds that students are coming from, as well as any educational gaps within countries. While comparing overall mean scores may be a useful tool to observe and compare the general achievement of a country, disaggregating the data may reveal new insights to the state of education within and across countries. This paper looks at how global comparisons would change if scores were disaggregated based on social class. Would the world’s leaders in education be the same if we were only looking at students from the lowest (poorest) decile? Using the 2015 PISA (Programme for International Student Assessment) mathematics scores, this paper will make global comparisons of disaggregated mean scores based on the PISA index of economic, social, and cultural status (ESCS). This variable was developed by PISA and considers occupational status and highest level of education of student’s parents, family wealth, home educational resources, and possessions related to “classical” culture in the family home (“Education at a Glance,” 2003). Using maps, this paper will visually display the differences in comparative achievement of students in the highest (richest) decile as well as students in the lowest (poorest) decile. This will allow the viewer to observe the shift in rankings and will challenge the preconceived ideas of who the global high achievers actually are. By disaggregating data, we get a fuller picture of educational achievement within countries and more points of analysis for cross-country comparison.

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