All 7 entries tagged Quantitative
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November 07, 2019
Previously I had discussed the limitations of thematic analysis, and briefly indicated how these limitations could be addressed using quantitative and patterned based approaches with the aim of generating a better understanding of the process of social learning processes as well as its essentials or essences. Although, I could argue in the thesis that in order to understand the process itself it is important to understand the essentials of the process relative to the research question and research objectives. How can a process itself be understood if we do not know its essentials? This is a question I’m currently thinking about.
Going further into the discussions, what I had found with the combined use of thematic, quantitative, and patterned based approaches is a more effective understanding of the process of learning, but still not a complete picture of the phenomenon as a whole. I am in a better position to explain ‘what’ happens and possibly ‘how’ something happens, but not ‘why’ that particular learning event happens at a particular point because I would need access to resources that have been beyond the reach and purpose of the Ph.D. However, in the thesis I am explaining all of this as part of potential future work that could be carried out. As individual analytical methods, not only did each in part support the findings of each other, but each approach offered a different yet compatible perspective of the data.
I had not anticipated or expected such vastly different perspectives of the data, so this complexity had overwhelmed me for quite a while. It took a lot of working out of the meaning of each approach and the data that each produced in order to understand how each set complemented each other, and what exactly the data was trying to communicate (and, indeed, the way I was interpreting the meaning of each set of data relative to each other). This is still ongoing and, hence, provides a possible reason to edit the findings and discussion chapters.
Let’s take a closer look at some of the philosophical and methodological issues of the combined approach that I have been thinking about.
Methodologically, the inclusion of multiple analytical methods does not constitute a mixed methods approach. Briefly, a research project could be considered mixed methods if each method is used with different types of data (e.g., qualitative and quantitative) leading to the production of different sets of data that is to me merged or combined in some way. Within this research, the qualitative thematic, basic quantitative and patterned-based approaches are being used with the same type of data and within the same type of general methodology (hermeneutic qualitative). A key question that I am currently exploring is whether or not this sort of approach can be considered ‘methodological triangulation’ or ‘analytical triangulation,’ or ‘multi-mode’ or ‘multi-methods’ research. Regardless, philosophically the multiple uses of methods is arguably compatible with middle-range realist perspectives as it is to my understanding that subtle realism (considered a middle range philosophy, and is a realist position I draw upon within the research) support multiple different types of analytical approaches within the same project in order to enable understand of the complexity of a phenomenon. I am still fully working out the compatibility between middle range philosophies and multiple uses of analytical methods within the same project, though I am arriving at the point that middle-range philosophical positions supports multiple analytical methods.
What does all this mean? What does or could this mean for qualitative research? My methodological position is hermeneutical and whilst most literature I have come across focuses on how hermeneutics assists with the interpretations of text, I am not convinced that this excludes some form of basic quantitative analysis. I am currently developing explanations and ideas about this, but my current thinking here is that because hermeneutics is compatible with middle-range realism, and because middle range realism advocates reasonableness and rationale development of concepts, the interpretations that are hermeneutically constructed can be supplemented or supported in some way by a form of quantitative analysis. This, of course, depends very much on the context of what is being explored. Because I am exploring a process of learning through accessing the process directly and not through some mediated access through, for example, the perspectives of learners, I can ground the research within a particular form of objective reality that can be supported in some way by the use of the quantitative. Through thematic analysis I can present a series of themes and codes, and make assumptions about a process based on those codes and themes, and then use the quantitative to provide a form of validating the reasonableness of at least some of these assumptions and interpretations, in conjunction with the pattern-based approach. This is again something I am currently figuring out.
The pattern-based approach provided a perspective of the learning process that differed widely from the thematic and quantitative approaches, and provided insights into the patterns and processes of interactions among participants that I had not previously anticipated and considered. This, admittedly, completely overwhelmed me as mentioned and for a while I was stuck and muddled, but I persevered and slowly, progressively, sense and clarity was being made out of the uncertainty. I am not yet in a position where I can fully elaborate on the way that the different approaches complement each other and build on the findings of each other, and what I have already explained might need editing. But I do believe that my philosophical and methodological arguments are becoming clearer as my understanding grows, and I do feel much more clearer on the meaning of the findings and the purpose of each approach compared to a few months ago when I felt completely overwhelmed with the differences in the perspectives that were afforded by the different analytical methods.
I still feel I have a long way to go, yet I also feel I have come really far. It is very wrong to think at any time that you are absolutely correct and absolutely close to where you need to be, because you can never really fully tell the distance that you are at compared to the complete whole. All you can to is track and trace the distance you have travelled, and if you can observe real difference and real progress in your understanding of everything that you do, then you’re on the right track!
February 21, 2019
During the past few months I have come to grips with what should be included in the literature review, taking into account its nature as part of an inductive, thematic analysis approach that differs from that which can be found in quantitative based theses. With quantitative based literature reviews, the goal is, quite generally, to critically explore existing empirical literature to find a very specific theoretical or practical gap in the collective understanding of the phenomenon of interest. Typically, this gap is then addressed through building a testable theoretical framework that essentially frames the findings and associated discussions. In other words, the theoretical framework predefines data characteristics and findings that are of most interest and use to the research and in answering the research questions that derive from the framework. There is a very strict order here: the literature is explored first, and from the literature review comes the theoretical framework, from the theoretical framework comes the research questions, and as data is found relevant to the research questions their discussion context is framed by the theoretical framework. Every part of the research, as far as I can understand, is framed around the selected theories that guides data analysis.
Inductive based qualitative literature reviews are different in that there is no predefined theoretical framework that is developed, and, therefore, there is no need to test theories or have any discussions and findings framed around existing theories. The core aim of inductive based qualitative literature reviews, from my own understanding of them, is to establish the general overall context of the research and to justify why the research is being carried out. Arguably then where quantitative based literature reviews are used to develop a deductively testable theoretical framework, qualitative based literature reviews are used to establish a justifiable context for inductive analysis (though do note that the theoretical framework still needs justifying!).
With all that then, I am using the literature review to explore the broader questions. For example, with the specific technology I am using to facilitate social learning processes I am asking questions about how that piece of technology has been used more generally in Education. In what way has the technology of interest been used for so far within the context of social learning processes? What are the differences of use of these processes between different technologies and what makes a particular technology of interest more appropriate? What definitions have been provided regarding the particular social learning process? How have these social learning processes been realised in various learning scenarios through technological facilitation?
Questions like these assists with building a picture of what has been achieved before and be able to set the research within a justifiable context. For example, through asking how social learning processes have been realised and explored in various learning scenarios, you begin to understand how social learning processes have been approached, defined, and understood. From this understanding, you can begin to critically question this understanding and of what exists, and this in turn leads to locating your research within the existing literature with justifiable supports.
The literature review is still ongoing although much of it has now been completed. There is still a couple of concepts left to explain, but this can occur at a later time. The core of the literature review has now been completed!
April 04, 2018
This past weekend has encouraged me to re-evaluate and re-explore the value of using both quantitative and qualitative data within my research project. This is an ongoing task that demands careful and reflective thought, and currently constructing diagrams that illustrate aspects of the design and the way in which these different aspects relate to each other, and the way in which the research shall now progress. Once I have completed these diagrams I shall be sending them to my supervisor for further feedback and confirmation of the design’s suitability. There are, not surprisingly, many thoughts, questions and ideas that I have about the emerging research design. As mentioned, going through all these thoughts, questions and ideas is an ongoing process but there are some key questions and ideas that I am focussing on at the moment with regards to the characteristics and aspects of the research design.
Firstly, and probably most importantly, should I reemploy a mixed methods approach? Is a mixed methods approach actually possible given the data collection context? Instead of collecting qualitative and quantitative data separately as is typically found in most mixed methods research, I have collected qualitative data and from this data set, both qualitative and quantitative data analysis shall be applied. I have a vision about what qualitative and quantitative data I want, but I am working through how this is going to be precisely and exactly realised particularly the quantitative aspect. I realise therefore I am not using mixed methods at the data collection level, but there appears to be a mixed approach at the data analysis methods level. This has implications at the methodology level: should mixed methods be confirmed as the appropriate approach to the research, then grounded theory becomes the qualitative method and not a methodology, whilst network analysis or some form of it becomes the quantitative method.
But here’s something to think about, and forms my second current thought and question: what comes between grounded theory and network analysis? What acts as the bridge that enables qualitative data to cross over into the quantitative realm? I think the answer lies in visualisation. In my understanding, a network is a visual representation or diagram of what is happening. A phenomenon can be understood through its aspects, features, events or activities and these can be represented as a network of nodes and connections. What I am attempting to do here is convert the concepts, categories and their relationships, products of grounded theory analysis, into a network. I am slowly working through how these grounded theory concepts can be converted into aspects of a network and this is going to take some time, but currently I am thinking that concepts and categories can be represented by nodes, and the relationships between categories can be represented by connections between nodes. What I am also interested in is exploring the relationships between these nodes because it is at these points where interesting observations and values can be obtained, but I’ve yet to figure out the way this can be fully considered. I’m thinking at the moment these relationships shall be related to the hypotheses that shall be developed as well as the properties and dimensions of categories and might also might be involved with quantitative analysis. The quantitative analysis shall be used to analyse these relationships to determine the strength between different types of nodes within different contexts, but the exact relationships and hypotheses that are to be explored are undetermined at this time and shall be until the qualitative data analysis section has been completed. This in a sense brings me to a third concern I am working on.
If my research is to adopt a mixed methods methodology again, what type of mixed methods should it be? My previous approach to mixed methods was a sequential exploratory type where qualitative data were to be collected and analysed first followed by the collection and analysis of quantitative data. This was therefore sequential in nature but I am not sure at this time whether my mixed methods approach now would be sequential or transformative: sequential because qualitative analysis will come after qualitative analysis, or transformative because it might be that some aspects of the qualitative data might be transformed into quantitative data. Is this even possible? It is in some context but I’m not sure if my qualitative data will be able to transform into quantitative and I am probably unable to know this till the qualitative analysis phase is complete and I begin to really look at the findings. At a push at the moment I'd say sequential exploratory: might be best to design both types just in case!
There are many other concerns that I now have that I shall be exploring further as my thinking and experimenting of the potential mixed methods approach progresses: in what way should I now present my research questions? The research questions shall have to change to better represent a potential mixed methods approach as the questions cannot be purely qualitative: a question must be qualitative and another must be quantitative but derived from an overarching question that brings both together.
Also, what are the implications on the use of literature and the roles of the literature reviews? At the moment I cannot imagine there being too many changes because of the important role that grounded theory shall continue to play in terms of identifying the nodes and connections of a network, which shall subsequently have some form or forms of quantitative analysis placed onto it (is this really network analysis, or something else?) although I shall have to double check the role of literature within mixed methods research.
What about the product of or the outcomes of the research? What is the nature of theoretical development within mixed methods research? A key role of mixed methods as described in some of the methodological literature is to both build and test a theory and / or a set of hypotheses. The qualitative aspect builds theoretical constructs and hypotheses and the quantitative strand tests these theoretical constructs and hypotheses.
What shall be or should be the extent to which grounded theory is used? Should I use grounded theory to the extent that a general theme of the learning phenomenon can be established and use that as the basis of the network construction and exploration? Or, should I use grounded theory to the extent that categories, relationships and hypotheses can emerge from the data, but use an existing overarching theoretical framework to guide their use in the network construction, and use quantitative analysis to test the identified relationships and hypotheses that come from the qualitative stage? I am not sure at this time.
What about the case study methodology? Should I return to thinking about the value of a case study methodology with mixed methods approach encased within? There is some debate about whether or not a mixed methods approach really is a methodology and not just a strategy of the way in which methods are to be sequenced or arranged. I shall have to revisit this debate area.
I have so many questions at this time, so many more than answers but I have a plan to work through all these different questions and issues that I have discussed here and more besides. I shall probably be writing on here on a regular basis now if only to document this challenging yet exciting journey and therefore to help me reflect upon my ideas and their development.
Thanks for reading! If you’re on your Easter holidays still, continue to have fun!
Not only have I been stuffing my face full of Easter goodness (hot crossed buns and Easter eggs) but given that the newly added methods to my research design have been confirmed and accepted as being appropriate as a result of coming to know the phenomenon of interest in a way I had not previously considered, I have been rethinking the structure and process of my research design. This is particularly since this past weekend where I had the revelation that perhaps I should return to and re-evaluate the value, worth, role and purpose of combining qualitative and quantitative data within my project. A current task is therefore to think very diligently, carefully, strategically, and comprehensively about how qualitative and quantitative methods can analyse the data, and how qualitative and quantitative data can be combined or utilised in a way that can comprehensively describe and explain the phenomenon of interest unachievable by a single approach.
An Emergent Research Design?
What has struck me recently is that my research design can be characterised as emergent. The newly added methods and the possible re-evaluation of the methodological approach has emerged from further understanding of the data, further understanding of existing literature, and further understanding of the different types, structures, processes and outcomes of the phenomenon of interest. Further, these sources appear to triangulate to provide some sort of justification for what has emerged e.g., what I have observed in the data and the need to explore these observations further can be backed by existing literature, and both give rise to the need of the additional data analysis methods and perhaps a rethink of the methodology and research questions. This idea of an emergent research design appears to be a characteristic not just of grounded theory but qualitative research design more generally.
Essentially and I shall be writing more about this in the future, the research design emerges as the data analysis progresses with further readings as necessary to support the need for any emergent research design aspect. Where I am now with the research design and the inclusion of network analysis as a method has come from what I have observed in the data. In other words, the need for such a method has emerged from understanding the data, from observing particular patterns and trends, thinking carefully about the way these trends and patterns could be explored more comprehensively, and the potential value and worth their explorations might offer to the research.
Let’s take a brief journey in time to reflect on where I have been with the research design
The Journey of the Research Design so far
The Ph.D. research began prior to the Upgrade process as a mixed methods project, where mixed methods approach was introduced at the data collection level where the idea was to collect qualitative data from observations of the learning phenomenon and quantitative data from surveys. After a series of doubts started to creep in following the submission of the original Upgrade paper about the data collection methods and the context of the quantitative data collection and analysis aspect, and after discussions with the Upgrade member panel and the supervisor, the approach was dropped. The qualitative aspect was kept and therefore, grounded theory became the sole focus of the research design. Grounded theory became the methodology and its coding package became the methods of data analysis.
For many months after I began to downplay the relevance of mixed methods approach in my research and began to focus exclusively on learning about Grounded Theory and the way that I can utilise Grounded Theory within my research context, which again has been documented extensively throughout the previous year. I also began to realise and became aware of the complexity of my philosophical beliefs both at the ontological and epistemological levels though had not travelled down to the methodological and methods level because of my continued denial of the value of a mixed approach to understanding the phenomenon of interest. I did, however, later in the year and earlier this year seriously began to challenge the theoretical orientation of grounded theory and began to really believe that symbolic interactionism (the most common theoretical framework of grounded theory) was not compatible with the research context and began to search for other possible frameworks. Again this has been documented in earlier blog posts. I also began, through reading through more existing literature and the draft writing of earlier thesis chapters, to challenge my own understanding of the phenomenon of interest: the way I perceived it, the way I approached its exploration, and the way I could define it.
This led then to me challenging the way I had used grounded theory previously to analyse the data and I came across a startling thought: grounded theory could be used to recognise a central theme of the phenomenon of interest and theorise about the phenomenon around this theme, but I began to doubt grounded theory’s ability to theorise or hypothesise about the progress and process of the phenomenon of interest over a period of time. It was not, so I came to eventually realise, the central theme of the learning phenomenon that was the only product of the research that is of interest to me: it’s the way in which the learning phenomenon initiates and is sustained over a period of time. This I think is an area that is not addressed by grounded theory.
Where am I now with the Research Design?
Grounded Theory is still of interest and of importance to the research in terms of, from what I can currently understand, identifying a central theme to the phenomenon of interest, and to theorise about the phenomenon in accordance with this key theme. However, in what way do I explore the progress of the phenomenon of interest and the way in which this learning process can be sustained over time? This is where network analysis comes into play. But here is something else: I have always created diagrams and “networks,” if you will, about what is occurring in the data in order to help me understand what is going on in the data but I had not considered these diagrams as being somewhat of an independent data analysis method in their own right as I always thought of them as part of the grounded theory. But as I drew out more of these diagrams I began to realise that I was making observations and identifying trends that perhaps grounded theory on its own might not be able to explore to a substantial extent. At least, not to the extent that I am now interested in.
More significantly, I’ve very recently began to think about the way in which I could use these diagrams to further explore the phenomenon of interest through network analysis and the inclusion of quantitative analysis to test hypotheses and theoretical constructs that have and shall continue to emerge through grounded theory analysis. And therefore, a reintroduction of an old idea: the mixed methods approach!
And that shall be the topic of the next blog post!
October 18, 2016
A couple of days ago it was a year since I laid out a few questions in a blog post that I was asking myself at the time regarding the role that researcher beliefs and perspectives of reality play in the research design. I thought I would provide an update on the current thinking regarding these questions.
First Question: Could a researcher, even within a Social Science discipline, really be objective?
Whilst this is being continuously thought about, at the moment I do not have the belief that any researcher can really remain objective, even quantitative researchers. When we talk about qualitative researchers, the argument is obvious in that objectivity is difficult to achieve although this really depends on the way in which objectivity is actually defined. For example, the nature of qualitative data requires the construction of a grounded interpretation of what the data is trying to suggest. Qualitative researchers construct meaning of the data, but this construction of meaning is an interpretation but grounded in the data.
It can be argued that it is this interpretation that gives the process subjectivity whilst the grounding of the interpretation can give research a sense of objectivity. This sounds similar to retroductive and abductive analyses and to some it does not make sense, but it is making increasing sense to me as it appears in my opinion to be good common sense to continuously construct an interpretation and ground any beliefs that stem from that interpretation in the data. Grounded interpretation means all beliefs, thoughts, ideas, and so on, coming from an interpretation that do not fit within the data itself should be discarded. This however does not necessitate the use of grounded theory but everything that is observed must be grounded in the data in some way.
Even social scientists using quantitative data could be viewed as subjective because from a broader sense the research questions and the fact that the social scientist has decided to use quantitative approaches is subjective because it is based on the way that they understand the research problem and the research question. So, whilst an experimental or quasi-experimental and other positivist, objective leaning approaches do collect and analyse data in a matter of fact way, the way in which those findings can be applied to different situations and indeed the way in which the findings are perceived will differ between social science researchers, in my opinion.
What I am considering further is the way in which we really relate to the data and therefore the way in which we interpret the data, and this is important for qualitative researchers. What is the relationship between the researcher and the data, and what factors are involved with such a relationship?
Second Question: Is a researcher drawn towards research methodologies more so because that methodology and methods match their framework of perceptions, beliefs, perspectives, values and attitudes of and towards reality?
Though I am still thinking about this, I would say yes: a researcher is drawn towards not what is actually best to answer a research question and to solve a research problem but is drawn towards that which best aligns with a researcher’s framework of perceptions, beliefs, perspectives, values and attitudes of and towards reality. But what are we talking about when we are talking about perceptions? Perceptions of what exactly? The research problem? Our own interpretation of the research questions that we ask? Where do these perceptions come from and what is it that we are meant to perceive? In what way do our perceptions influence our beliefs, values and attitudes?
My Philosophical perspectives have changed during the past year from constructivist to critical realist because I have come to realise the complexity of reality relative to the phenomena of investigation; that neither exploring the process of the phenomena nor exploring the experiences that people have of the phenomena are enough to gain a full understanding of the phenomena. Risk taking has and still is involved, but so far I think I am on the right track with my philosophical and methodological development and development of argumentation for them. It’s been especially easier since dropping case study. Well, that’s the other issue: sometimes we can become quite set on a particular methodology that we come across difficulties and struggles when we attempt to integrate particular methodologies and methods with other methodologies and methods, but this really depends on the way in which methodologies and methods are used. E.g., I was proposing to use a case study approach as a strategy for question formation, data collection and data analysis but came to the realisation that it was not compatible with grounded theory therefore dropped all case study elements. Since then in my opinion the methodology has been more workable.
I suppose we could say that researchers are initially drawn to methods and methodologies that meet their frameworks of preferences, but then later when they really begin to think about their design, the phenomena and the context of exploration they begin to understand what really might or might not work.
Third Question: Are we as individuals within our society really able to reach or understand objective truth about reality, or will people forever be led by their own preconceptions, perspectives, values and attitudes of and towards reality?
Answer to this for me is a lot more stable than it was a year ago: from a critical realist perspective the answer is, whilst objective truth about phenomena might be out there independent of our thinking, experiencing and perceiving such phenomena, our understanding and knowledge of this phenomena is subjective and always prone to fallibility and defeasibility. This is exactly because our personal frameworks of observation and understanding reality are based on our own experiences of and interactions with reality.
Fourth Question: What should be the extent or role of a researcher’s subjective framework of beliefs of reality play on their role of being a researcher and the development of their research design?
I have the current belief that this is really down to the individual researcher to decide. For me personally, my philosophical and methodological approaches have changed as my own understanding of the phenomena and the context and situation within which the phenomena are to be explored has increased and developed. Has the research design altered based on my own framework of beliefs of reality? You could say yes, but then can also abstract a step higher and say that the research design has changed because of being open minded, cautious about being absolutely certain about research designs, and the willingness to change beliefs about reality: to let my understanding of the phenomena and its explorative context influence my beliefs about reality and therefore about the way in which reality and the phenomena, is to be explored and should be explored.
Thinking about the role of the researcher, the relationship that the researcher has between him/herself and the participants and between him/herself and the data is a current topic of thinking and consideration for my research. This is because if we do not think about ourselves as researchers, our positioning within reality, the way in which we view data, and the way in which we view research designs we are in danger of becoming stagnant and willing to accept any design that we come across just because it basically works. But, this pragmatic approach to “what works” does not necessarily mean that it is the right or best suitable answer.
‘till next time: keep designing!
January 09, 2016
Introducing Triangulated Mixed Methods Methodology
Ta da! This has come as a breakthrough for my research as I have now identified what I believe to be the research methodology that is most suitable for my research. Triangulated Mixed Methods is a research methodology that applies Triangulation approaches within the context of Mixed Methods research, which essentially according to some writers enable higher levels of validity and reliability through comparisons and corroborations of differing types of data from different sources, which exactly matches my vision of my research project.
From the initial rereading, Cresswell provided the clearest and most useful definitions of this type of Mixed Methods methodology that convinced me of its suitability. Cresswell describes Triangulated Mixed Methods Methodology as suitable for research projects involving comparisons, validations and expanding discussions between quantitative and qualitative findings. This is suitable for my project because it will involve comparing quantitative data with qualitative data and using these further analytical comparisons and discussions to expand on separate analyses and discussions that shall be made with each data set in the thesis.
There are other reasons, but that was the major, influential definition of Mixed Methods that has encouraged the favoured methodological view to Triangulated Mixed Methods.
What does all this mean now for my research Methodology and research Philosophy?
In brief: Triangulated Mixed Methods methodology is now the research methodology for my Ph.D. with Constructivist Grounded Theory now being used as a research method along with questionnaires. Interview and focus groups shall be used in addition at a later stage as and when deemed necessary. This obvious impact on my methodology will have an impact on my research Philosophy, although the Philosophical assumptions and perspectives of Triangulated Mixed Methods, and Mixed Methods in general, appears to be highly discussed and debated by a lot of authors and Philosophers (oh fun!)
So will this methodology make reality any easier to understand?
Er, no, well, it will, eventually! Basically, even years before starting the Ph.D. I had an idea that my research would be quite complex because what I am doing is exploring perceived learning (quantitative data, qualitative data) and actual learning processes that take place (qualitative data, mostly). This direction has not changed; it has only became more specified and detailed but I am not going to discuss the specifics on here: I shall leave them to my future published research papers and thesis. The methodology now selected makes a lot more sense to me because it allows me to investigate the phenomenon in exactly the way that I envisioned.
Loads. Sheer absolute loads to do, which is fine because it gives me plenty of blog material! Methodologically speaking, I need to select the most appropriate variant of the Triangulated Mixed Methods methodology to use, as there are several variants that have been designed and debated, although I already have a fair idea but need to do more reading and experimenting into this. Also, I need to identify Philosophical assumptions and develop Philosophical arguments for using Mixed Methods methodology and this shall take a little while given the amount of debates from various authors. Following this, I then need to carefully plan the way that Constructivist Grounded Theory and Questionnaires shall work effectively within a Triangulated Mixed Methods methodology, and carefully think about the practical assumptions and considerations that Triangulation makes upon the data analysis. Not only this, but I also need to carefully consider the Philosophical assumptions, arguments, practical applications and so on of both Constructivist Grounded Theory and Questionnaires and the way that a Triangulated Mixed Methods methodology actually bring these Philosophical and Methodological differences together in the way that research objectives are achieved.
Additionally I need to carefully consider the way in which the methodology and methods all come together to deal with issues of data validation, integrity, reliability, consistency, coherence, authenticity, and so on, and also develop ways in which challenges that each method and the methodology provides shall be carefully managed, maintained and dealt with so that any data errors are avoided as best as possible.
All this and much more shall be considered within the thesis and various research papers that shall be published from the research. Now that the methodology and methods are set, I can begin to think about, within the context of my research, all these Philosophical, Methodological and practical issues and much more than has been discussed here as I think I have wrote enough about the subject for the time being!
‘till next time: is there really such a thing as objective reality?
November 29, 2015
Regular readers will have probably noted the discussions I have made (or starting to make) about the Philosophical difficulties of integrating quantitative and qualitative data in a single research study, relating mostly to the fact that quantitative is usually associated with the Positivist perspective whilst qualitative is usually associated with the Interpretivist perspective. But what I have not really touched upon at all are the difficulties of the methodological perspective (yes: there are Philosophical difficulties AND methodological difficulties, and both appear to be related to each other: check earlier blog entries that discuss relationships between Philosophy and Methodology). The methodological perspective is beginning to gain more attention as I come to understand Grounded Theory, and a couple of questions that have come to me are: what methods are appropriate for data integration? Along with, which methods are suitable for my research?
With the data collection this is no longer a problem: a mixed data questionnaire shall collect both qualitative and quantitative data and an extra method or couple of methods shall be used to gather more qualitative data. Quantitative data shall be analysed using a series of different statistical methods (descriptive statistics and also methods to identify and analyse relationships between different identified variables), whilst qualitative data shall be analysed using a series of analytical methods inherent to Grounded Theory processes (though there are some debates about the usefulness of some methods depending on the context of the research). Essentially, Grounded Theory involves interpretation of the collected data, and to develop codes and categories using the coding methods in order to explain or describe what is actually going on within the data. These codes and categories are developed for each qualitative data set and then compared across each set using a method called “constant comparison.”
Describing the “constant comparison” technique is way beyond the purpose of this blog post, but it suffices to say that it is used as a mode of comparing codes and categories across data sets as part of the process of continuous and simultaneous data collection and analysis, in order to develop a theory or to theorise about what is going on within the data. It’s a bit more complicated than that but for now that’s the best way that it can be described rather briefly. The point I am trying to make here is there has to be a way to generate codes and categories from statistical, quantitative data in a way that is comparable and compatible with codes and categories generated from qualitative data, in order for constant comparison to be utalised across all data sets produced from all data collection methods. If this is possible within my own research, then the theory or theorisation that shall occur as a result of analysing and integrating different data sets shall increase its reliability, validity, and possibly even generalisability. But this is something that I shall need to work out and perhaps it might be related to the quantitative methods: could I create comparable and compatible codes and categories from descriptive statistics? Could comparable and compatible codes and categories be generated from relational descriptive data analysis such as, say, the likes of ANOVA? What about regression analysis? Are codes and categories even meant to be compatible and comparable across differing data sets? If not, then in what way can a theory or theorisation even begin to happen if these codes and categories cannot integrate? What, exactly, is required to develop a theory or theorisation from a complete and cohesive collection of data? In what way can a collection of data be considered complete and cohesive? Does any of that even matter?
There are many many issues and problems, debates and perspectives relating to Philosophy and Methodology of data integration that shall have to be considered, and as you can imagine I shall probably banter on about them on here as and when I come across them! Regardless I do have the belief that I can create comparable and compatibles codes and categories across all data sets. I have the belief that Positivism and Interpretivism in some way can complement each other rather than compete with each other. But I do not know this for sure at this time: this time next year I might have a completely different picture of the way that Grounded Theory works and the way in which integration of quantitative and qualitative data can happen and should be appropriate for the context of my research. But that’s the way research forms and develops!