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Abstract:
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"Instead of offering a comprehensive set of mixed method research designs, our goal is to offer some principles for deciding when mixed method projects are most approriate, and to distill these into suggestions for practice and evaluation. We start by defining mixed method research as the combination of qualitative and quantitative methods of data analysis within a single project. While we believe that this is the most commonly accepted definition, it is not the only one, and we explain the consequences of defining it in this way. We then present a basic decision tree for use in planning empirical research and we explain where, along its branches, mixed method research is most useful. Our decision tree introduces three proposes for mixed method research designs - supplementary validation, convergent validation or triangulation, and theory generation - and explains the kind of claims associated with each. This tool can help the researcher produce more clarity about her intentions and in doing so, make it easier for others to evaluate the success of her project. Because researchers are often not explicit about their intentions, however, we conclude this paper with a set of guidelines for evaluating mixed-method research. Since the purposes for using mixed methods differ, we argue, the criteria for the successful use of mixed methods must differ as well."
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