MQIC 2019 Keynote Address
Dr. Pat Bazeley, Director of Research Support P/L and Adjunct Professor in the Translational Research and Social Innovation Centre at Western Sydney University
The MQIC 2019 will open with the keynote address by Dr. Pat Bazeley. Since graduating in psychology she has worked in community development, as an evaluation researcher, and in academic research development. For almost 30 years Pat has been providing research training and project consulting to academics, graduate students and practitioners representing a wide range of disciplines across Australia and internationally. Her particular expertise is in helping researchers to make sense of qualitative, survey, and mixed methods data, and to use computer programs for management and analysis of data.
Pat’s research has focused on qualitative and mixed methods data analysis, the development and performance of researchers, and the wellbeing of older women. She has published books, chapters, and articles on mixed methods and qualitative data analysis. She serves on the Editorial Boards of the Journal of Mixed Methods Research and Qualitative Health Research, and was 2015–2016 President of the Mixed Methods International Research Association. Currently, Pat is working on a second edition of her book, Qualitative Data Analysis: Practical Strategies (Sage, 2013).
“Transcending the qualitative-quantitative divide: Implications for data, methods, and software”
Mixed methods research is commonly defined as involving a combination of quantitative and qualitative methods to research, yet the boundary between these is far from clear. They are better described as broad approaches rather than definitive methods, each of which is a way of representing the world and phenomena within it. The world is not easily divided into quantitative and qualitative elements, however; rather all phenomena within it are multidimensional, capable of being represented through a broad array of methodologies and methods, any of which is inevitably partial. By subsuming all approaches (e.g., including visual methods, historical methods) within a quantitative-qualitative framework, we lose something of the unique perspectives and methods these approaches bring to understanding other dimensionalities of phenomena (such as colour and form, age and permanence).
In this presentation I argue, therefore, for a broadened understanding of what mixing methods might mean and for the legitimacy – indeed, the necessity – of mixing methods, if we are to begin to genuinely represent the full richness and meaning of the phenomena we study. Such an understanding and approach has implications for data choices, methods employed, and software use.