Students' Emerging Reasoning About Large-Scale Data Tables

Abstract

The open data movement makes unprecedentedly available a large-scale of authentic data sets on a wide range of social important topics. Competent use of large-scale data predominantly requires comprehension of tables and other visual data representations. In this paper, we examined tabular understanding of a group of thirty-two 15-year-old students in Cyprus, while they were investigating tables of real data published by EUROSTAT, the statistical office of the European Union. Participants investigated trends in real data displayed in tables, and reflected on the components of population change in several EU countries, including natural increase of population, net overseas migration, and total population growth. Our analysis of the participants' reasoning indicate that four levels of data-table comprehension, in line with Shaughnessy's (2007) framework for smaller data, emerged.