A practical, iterative framework for secondary data analysis in educational research

Abstract

Secondary data analysis in educational research has been an established research method for many years. Yet, few publications outline the “how to” of undertaking the process. This paper presents an analysis framework suitable for undertaking secondary data analysis within the field of education. The framework is a modification and an application of a pre-existing data mining research process known as Knowledge Discovery in Databases (KDD). The KDD process is interactive and generative and involves a series of sequential steps and decision-making processes. The modified KDD process is described to show how it supports secondary data analysis and provides an example of how the modified KDD process was applied across a secondary analysis in mathematics education. This paper provides educational researchers with a practical and iterative framework through which to undertake secondary analysis that enhances flexibility and encourages depth and saturation.