All entries for Sunday 17 January 2016
January 17, 2016
The Ph.D. is not just about generating new knowledge about a phenomenon: it is also about being engaged at the Methodological and Philosophical levels. Being engaged at the Methodological level means really thinking about the methodologies and methods that have been used to explore and develop new knowledge about the phenomenon of investigation. The uniqueness of a Ph.D. therefore lies not just in thinking about it in terms of developing new knowledge but about the way in which this new knowledge is developed and understood. Being engaged at the Philosophical level means to think about your own perspectives of reality, the way that knowledge of this reality is collected, and understanding a variety of different Philosophical perspectives of reality and their relevance towards the research project along with understanding the way in which your perspectives of reality influences research design. This post shall deal with being involved at the Philosophical level.
Previously I thought of myself as a constructivist, an interpretivist, a relativist and a contextualist. I began to reject the notion of an objective reality and therefore had the idea that we create or construct our own reality, that therefore reality is a little different for each of us and that the way we come to understand and attain knowledge within this reality is different for all and our perceptions of the usefulness of related processes also differ.
This view was initially reflected in my own research design through favouring a qualitative methodology and using qualitative based methods to explore the phenomenon of interest. As time progressed however and a more significant understanding of the research problem and research methodologies was attained, I began to grow an appreciation for quantitative methodologies and methods. Philosophical and Methodological battles therefore began to occur as I attempted to understand the way that quantitative data could be included in a qualitative methodology. These battles were a reflection of the fact that what was occurring was going against the way that I perceived the relationship between reality and research exploration with Social Science disciplines: that you cannot define behaviour and generalise behaviour of phenomena through using statistical analysis and relationship between variables. But the more I thought about this (and the more that I continue to think about this) the more that exploring particular aspects of the phenomenon using quantitative analysis made more sense. Using a methodology where quantitative and qualitative approaches complement rather than compete with each other made more sense when an aim is to attain a substantial understanding of the phenomenon.
There appears to be a group of researchers who subscribe exclusively to quantitative methodologies and methods and therefore perceive reality as absolute; that reality exists independent of our thoughts and behaviour of the mind and therefore can be understood through deconstructing or reducing reality down to a series of variables and exploring relationships between them. There is another group of researchers at the other side of the Philosophical and Methodological Spectrum who are exclusively qualitative; that they perceive reality as being relative and contextual, and that therefore each person develops their own reality within the context they are within. Then there are those in the middle who believe that reality can be understood through the complementation of both perspectives. Remember however that within Mixed Methods there can be no “mixing” or combining of these perspectives, only that they are used to deal with separate but related research questions and problem areas.
So where do I stand with all of this at the moment? I still consider myself as a constructivist: I perceive reality as being subjective, that each of us develop our own realities and that this construction of reality and reality itself is relative only to the context that we are within. But, I do and am beginning to value the quantitative relative to my own research problem and research question therefore I would place my own perspectives and research itself now towards the middle.
Note that I am not suggesting that all Ph.D. candidates should immediately start considering the middle as the answer to everything. Which side you place your research is influenced by your own stances and understanding of its Philosophy and Methodology, and a sound grasp, understanding, and critical analysis of the relevant, current literature. The research questions, the research problems, the research purposes, the methodology that you select, and methods that you adopt should be led not by your own agendas and Philosophical perspectives, but by the needs identified in the literature.
What are you really investigating? What do you want to investigate? What are the constructs of your research? What are your Philosophical views? What way do you perceive reality? What methodology are you adopting? What methods are you going to use?
All these questions, and more, should be led by that understanding of the literature, and your own biases and assumptions need to be placed aside as much as possible. But this is not always achieved, as even the most objective person has even the smallest amount of bias and favourability towards particular research methodologies and methods. Researcher bias therefore is a big topic of debate within academia and the way in which researcher bias influences the results and therefore questions are asked as to what influences researcher bias to occur in the first place.
It is challenging when you really start questioning your own perspectives because some can go into a complete denial about the complementary aspects of differing methodologies and methods, but this is a challenge that all Ph.D. candidates should tackle. Again, don’t feel that you should subscribe to a particular methodology or method just because it appears fashionable, but go with what is right for your own research questions and problem areas. Once you feel authentic, you begin to produce authentic work, and therefore raise the respect and authenticity levels of research work as a whole.
‘till next time: question yourself and your views of reality, and do what is right for the context you are in!
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.
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!