Using Big Data, Large-Scale Studies, Secondary Datasets, and Secondary Data Analysis as Tools to Inform Social Studies Teaching and Learning

Abstract

Secondary datasets, large-scale studies, and big data are attractive information sources that have the potential to broaden the scope and influence of social studies research. Using large-scale samples and complex sampling frames, secondary datasets offer greater external validity, considerably more variables, and more representative samples than primary data. Other advantages of secondary datasets are accessibility, time and cost savings; however; analyses of these datasets require knowledge of a wide range of statistical methods and modeling. Positioning the value of large datasets in examining the vox populi and the underutilization of large-scale studies and secondary data analysis in social studies, authors discuss possibilities big data offer the field, democratization of data, and repurposing of data. Limitations of working with large-scale datasets and statistical considerations to avoid pitfalls of secondary data analyses are presented. Authors conclude with the potential wisdom of democratic judgment derived from large-scale, data-informed thinking in social studies.