January 17, 2016

Methodology now in place: the convergent flavour of the Triangulated Mixed Methods methodology!

The methodology has been set in place and that is the Mixed Methods methodology; specifically, Triangulated Mixed Methods methodology (triangulation simply means to collect and analyse data from multiple sources using multiple methods in order to increase validity and reliability of the research findings: more about this shall be discussed in time). There are various flavours of Triangulated Mixed Methods each of which having a specific, clear, concise and contextually defined set of objectives therefore each flavour is suitable for a particular purpose. Out of all of these flavours I have decided to select the convergent flavour of the triangulated mixed methods methodologies.

Triangulated Mixed Methods Methodology: the Convergent flavour.

This convergence design has been termed in various ways in existing literature including “convergent parallel” design, but regardless the aim of this flavour is to converge quantitative and qualitative findings at the interpretation level. This shall enable the findings to be compared, contrasted, corroborated and related (hence convergence) in order to discover similarities and differences in order to increase validity and reliability of research findings (hence triangulation). But there are other interesting potential uses for this converged (or mixed) results such as developing further research methods to explore further aspects of the phenomenon that were not been previously considered.

Other varieties of Mixed Methods and indeed other flavours of the Triangulated mixed methods differ in the order of which quantitative and qualitative data should be collected and analysed, whether or not the quantitative or qualitative data should be independently collected and analysed or integrated at various stages, and the importance or weighting of both types of data. The Convergence model encourages the separate, independent collection and analysis of quantitative and qualitative data, but converge at the interpretation stage. The model also promotes a concurrent (where both quantitative and qualitative can be collected simultaneously within the same time phase of the research) approach to collecting data instead of sequential (quantitative then qualitative or qualitative then quantitative). This means that the findings of the quantitative does not influence the findings of the qualitative, and vice versa. Basically they are both collected at the same time, but do not influence each other or data collected using other methods. What this can do however is influence the design of any further methods that might be used throughout the duration of the research. Further to this, the model also encourages an equal weighting of quantitative and qualitative data in answering research questions and dealing with aspects of the research problem.

More questions!

The key decisions have been made with each decision bringing about more questions and challenges that need to be addressed, but this is the case with all decisions made about research design. If you are not generating any questions about your research design as you go along then your inquiry into your own thinking, perspectives about reality, purposes and uses of your own design and a complete and full understanding of the underlying problems and questions and the relationship between these and the design shall be unguided and chaotic. Questions bring order and a sense of direction to any research project, that their development and refinement are continuous, and is something that each Ph.D. candidate should be engaged with at all levels and stages of their Ph.D. research.

Therefore, the selection of the Mixed Methods methodology, the selection of the type Triangulated Mixed Methods, and the selection of the Convergent flavour, along with the previous selections of specific methods that shall collect quantitative and qualitative data and the ongoing decision making regarding data analytical methods, introduces many more challenges and questions than answers! There simply does not appear to be any right or wrong answer or approach to deal with any of these challenges or questions: what therefore needs to be done is attain a full understanding of each challenge and question, carefully read and analyse relevant literature, and develop a solution or answer with suitable argumentation.

Key questions are: could mixing of the data occur at both the analysis and interpretation stages? Would this approach to mixing be appropriate for my research? What could the potential findings be? What implications could this have on any aspect of the research design? What implications could this have on the rigour, validity, reliability, generalisability, completeness and comprehensiveness of the findings, discussions, and research design overall?

I am not in a position to answer these questions yet, but they along with all other questions and challenges, and every other question that shall occur in the future, shall be answered in time!

‘till next time: let your research design be guided not by your answers but by your questions!

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