Dr Judy Rose
Assoc Prof Sama Low-Choy, Dr Toni McCallum, Daniela Vasco, Eunjae Park
This mixed methods 3-part course is designed for participants wanting to understand the principles and practicalities of combining qualitative and quantitative techniques.
Part 1. The course begins by reviewing key literature on the theoretical foundations of mixed methods research. Next, it examines mixed method case studies including qualitatively-driven, quantitatively driven and other mixed method designs. Finally, we demonstrate concrete techniques for developing a conceptual framework that potentially helps bridge between qualitative and quantitative methods, and can help structure the literature review.
Part 2. We show how a common conceptual framework can be constructed to inform both qualitative and quantitative analysis, including Bayesian statistical modelling (Low-Choy et al, 2017). This includes identification of variables and describing their relationships, as relevant to the research questions. We will pay particular attention to how the conceptual framework can be used to structure and guide the literature review, including its breadth and depth, building on Pickering & Byrne (2014). Altogether we show how this provides a basis for graphical forms of modelling, from Structural Equation Models, to Bayesian Networks or Bayesian statistical models.
Part 3 of the course guides participants in how quantitative and qualitative components can be put together in modularised, nested, embedded, and integrated models. The course culminates with participants diagramming a mixed method research proposal. This course is suitable for those new to mixed methods research along with those who have tried it ("dabblers') but would like to learn more.
External participants are welcome to attend.