All entries for April 2018
April 21, 2018
What a busy time it has been since I wrote the previous couple of posts about my new research design. I am thinking about this new design constantly and I shall be writing more about the design following on from the previous blog posts in due time, but it suffices to say that the blog posts relate to the second part of the new research design: the graph theory / network analysis stage. The idea at the moment is to convert what shall be the developed grounded theory categories into elements of a network and perform, where and as deemed appropriate, various numerical and quantitative analysis upon the data. I have picked up some really interesting papers and other resources about this so far and some I shall share when I get round to writing the blog posts about the networking side of the research design. I am not entirely sure if it will be mixed methods or multi methods as the need shall emerge from the data analysis but I shall discuss this in future blog posts.
Attention for the time being has been shifted to the rewriting of sections of the second literature review chapter, where I am discussing and exploring specifically the phenomenon of interest and related constructs. The main focus at the moment is continuously rewriting the first section of the second literature review chapter that focusses on the main phenomenon of research interest. I am furthering my exploration of literature and this is leading to a deepening of my conceptual understanding and the potential nuanced existence that the phenomenon of interest takes not just in its own existence but in its co-existence with other learning phenomenon. This is an ongoing process, but this continuous exploration is helping me to further contextualise my discussions of the phenomenon and to really understand the way that this phenomenon fits the context of the research. This first section is important, because it revolves around the reflective, analytical, evaluative and critical exploration of existing conceptualisations and definitions of the phenomenon of interest, the different kinds, and the different ways in which it has been applied within general educational contexts.
The more I develop my depth and breadth of understanding the phenomenon and the more I deepen my explorations into literature, the more I can deepen the breadth and depth of my conceptual understanding, of existing and relevant arguments and debates and engage with them accordingly, and further develop justifications for exploring the phenomenon of interest in the ways that I am presenting. This has always been a long term, continuous process and it continues now, and I am really beginning to observe and understand its complex existence and that it’s part of a complex network of learning phenomena. I am asking a lot of questions about the potential product of the research and the way that the emerging theoretical framework shall be situated between other theoretical frameworks related to exploring other learning phenomena, and therefore the way that it competes with or complements the use of other frameworks. I’m going in directions here I never thought was possible even just a couple of years ago.
As for the process of rewriting the literature review sections, I’ve basically more or less completely rewritten each drafted section completely and continuously extending, amending, and further adding arguments and ideas. Sometimes this can take up the majority of your reading and writing sessions: I spent a whole day recently rewriting a single section because as I was able to develop a concept, idea, argument or critical commentary of a piece of literature or existing argument I was finding that I could reference different aspects of a piece of literature and the ideas and critiques in other areas, effectively leading to a domino effect or a chain of increased idea development across all aspects of that section.
It is a complex process that is continuously driven by the following questions: is what I am suggesting here accurate and correct? Is this the way I am really going to present my argument and critiques? Is the order of the current section logical? Does everything flow and connect appropriately? Does everything communicate exactly what I want to say at that specific time? Is there a way I can better present and build upon my ideas? Can I present my arguments better? Can I improve upon my arguments? Can I in some way enhance them? How can I enhance them? Have I gone deep enough? How do I go deeper into my arguments and ideas? How can I draw out fully the depth and breadth of my ideas and arguments, and their relationships? How do I know when I have achieved the ultimate level of depth and breadth? Is this even possible? How do I know if this is possible? How do I know that I know what is or is not possible? How can I use further literature to support my ideas? How can I use existing literature in different ways? What else do I need to do in various sections? Can I further the logical connections between ideas? Can I present these logical connections between ideas differently? Is this current structure the actual structure of the chapter?
When you think about it though, most of these questions are not just associated with the literature review chapters but every single chapter in the thesis and every single section of each chapter. This is where a line by line, sentence by sentence analysis is coming in handy because I am questioning the purpose, meaning, value, and worth of every sentence. I am questioning the linguistics, grammar, content, accuracy, validity, verifiability, and epistemic stance of each and every sentence. All guided by the questions just mentioned.
Is it taking me a long time to find that happy point with that particular section of the literature review? Yes I think so, but I think I am getting there now and I believe that I have the grounds upon which I can build the rest of the chapter and that might now mean rewriting the other sections of the chapter completely. I have another section that has developed substantially and other section that is in need of a lot of work, but that doesn’t really matter so much now because I can approach the rewriting of other sections within the context of the first section. Remember, everything has to be connected and flow logically. In my opinion there is not a high amount of value in writing disjointed and disconnected sections: you have to write each section in accordance to the first, because it is the first section that really should set the scene and contextual layout for the rest of the chapter sections.
Ongoing and challenging process, yet it is satisfying and a relief when you can observe substantial changes and improvements to the way you are writing your chapters and the way in which everything you want to say is being communicated.
‘Till next time!
April 08, 2018
In the previous blog post I talked about the role and function of Open Coding, which is to label data segments with meaningful codes that summarise the content, features, characteristics, events and activities within that data segment and from these codes, develop categories and their properties and dimensions. Remember that categories are a collection of similar codes, with data segment characteristics represented as properties and dimensions. Open Coding from what I can understand is essentially descriptive where it attempts to describe the features and characteristics of data through coding and category development, and as argued by some authors, carries realist assumptions based on its use of constant comparative analysis. I did ask questions about where to go next following Open Coding, and now I think I have the answer.
I had my doubts about Axial Coding initially simply because of the challenges and criticisms against Axial Coding from various authors, who shall be engaged with on here at some point and especially in the thesis. But you should never adopt or reject an approach just because others have criticised it: you should instead adopt or reject an approach based on its relevance and suitability for your research project. As long as you justify and reason why (and why not) you have used (or have not used) particular design components and that they are aligned more generally with your philosophical and theoretical (if appropriate) assumptions then you are within your right to use any coding form.
I have now come to the idea that Axial Coding is the most sensible next step level of coding for my research. Open Coding then is that descriptive approach to developing categories; Axial Coding, therefore, is a more abstract means of coding that involves linking or relating categories together in order to better understand a process not through the views and experiences of those experiencing a process, but through exploring the process itself. Axial Coding is beginning to be understood therefore as a means of developing relationships between categories, and of developing relationships between a category and its own properties and dimensions.
During the process of redeveloping my understanding of Open Coding, conceptions of categories were formed: what a category is, what information should best be part of a category, and the guiding questions I have when developing a category further in terms of its properties and dimensions. I have noticed upon further reading that some of the questions I ask of a category, some of the questions align with the purpose of Axial Coding but that’s fine as some authors have stated that the thinking about relationships between categories and between a category and its own properties and dimensions occur during the Open Coding stage. As I recode the data I shall have additional questions though, and are based on the development of the relationships and they include: what forms a relationship? How can I identify a relationship? What is the content of this relationship? What are the features and characteristics of this relationship? What is the influence and impact of the context of the situation upon the relationship? Axial Coding, then, not only establishes relationships but also appears to acknowledge and consider the context of the relationship. For example, a relationship between two categories might differ between different contexts and this is important when exploring learning phenomena.
Although Axial Coding can establish and identify relationships between categories, properties and dimensions, it does not, as far as I can currently understand, produce an actual network of activities and events relating to the sustainability and on-going nature of social learning situations but it can provide the foundational understanding of what is occurring within a discussion through categories, dimensions and properties. However, it might be possible that a grounded theory’s relationship identification process and network diagrams and associated analysis attains a better understanding of certain social learning processes.
This is simple a try it out and find out approach, but from what I have drawn out in a presentation that I am producing for the topic it appears that this is the limitation of grounded theory and hence the introduction of a network analysis method and the interest in quantitatively analysing relationships but this is for another blog post.
In all, Axial Coding makes more sense to my research now if I view it as a means of relating categories, and to relate categories with their properties and dimensions. This makes sense to me because clearly defining relationships between categories and their dimensions and properties shall assist with understanding the complexity and highly nuanced existence of certain learning phenomena and provide a basis upon which I can build complex networks and be able to quantitatively analyse the relationships between these categories.
That’s the picture of Axial Coding for now!
‘till next time!
April 06, 2018
There has to be a sense of emergence where codes are derived from data and categories are derived from codes. This idea of emergence makes sense as I have not been able to identify an existing framework that is suitable and relevant for the type of data I am using and the way that I am now exploring the phenomenon of interest, and therefore, theoretical constructs, relationships and hypotheses must emerge from the data.
I read an interesting paper the other day where an author aligned the idea of an emergent approach with the realist ontology: truth emerges from the data after a continuous cycle of coding and recoding, but this brings about a couple of problems. First of all, what is defined as truth and of being true? How can it be measured? How can I know that something is true even after going through continuous cycles of coding and recoding? How can I know that this truth emerges from the data and not simply a reflection of my interpretations of the data? Is it absolute truth that emerges from the data or is it that with each coding and recoding I could come closer to the truth without completely attaining it? How do I know either way? Is there some set criteria for truth? If so, then would this criteria itself represent truth if it’s simply been constructed by another human being? Would it therefore be better to consider the set criteria is bringing one closer to the truth rather than mirroring the location of absolute truth?
One thing I do know is when I think about the qualitative strand, the purpose that it brings to the research, and what I currently would like to achieve with the strand, allowing the data to speak for itself; to enable this “voice” to emerge naturally and to code in accordance to what is believed to be occurring within the data makes sense. And this is where it is interesting because some authors suggest that enabling the data to speak for itself (please note that data do not literally speak!) and to therefore let understanding and meaning emerge from the data, but it is clear that there is an interpretation process happening. We as researchers interpret what we are observing in the data and attach to chunks of data what actions and events we believe are occurring within that data segment. Question here therefore is what is the relationship between truth and meaning? Is meaning objective and already exist within the “voice” of the data? Or, do we define meaning and apply it to what we perceive or interpret to be happening within the data? There are techniques within grounded theory such as theoretical sampling and constant comparisons that provide some answers to these questions but to what extent is truth realised by just grounded theory alone? Can ultimate truth really be attained?
What is the purpose of the qualitative strand within a mixed methods approach? From what I have been rereading, mixed methods can be used to build and test a theory, theoretical constructs, relationships and hypotheses. Their development occurs in the qualitative strand and then tested in the quantitative strand, and therefore adding an extra dimension of richness, integrity, authenticity, verifiability and validity to the research design.
A question I am working on at the moment given that Grounded Theory is part of the qualitative strand is to what extent do I use grounded theory? I have now more or less worked out the initial phase of qualitative data analysis, and this initial phase shall consist of Open Coding also known as Initial Coding. I think this is more or less a definite because it is through Open Coding or Initial Coding that meaningful data segments are labelled with suitable codes that describe what is happening; where a technique known as constant comparison is used to identify similarities, differences and variances, and where (in broad terms) these similarities, differences and variances contribute towards categorical development. I have recoded my data a few times and so far I have lots of codes, and some initial categories developing but shall now have to recode the data since developing new ideas about the research design and about the way I want to explore the phenomenon of interest. And also because I understand the data more now. This leads me to an interesting thought: not only do our theoretical understanding of what is occurring in the data develops over time along with the need for particular research design elements (assuming emergent research design), but also understanding of the data itself emerges from the way that we perceive and interpret what is going on. There is an interesting relationship going on here between our own perceptions and interpretations, the development of these perceptions, and the data itself. What role does the data play in this relationship?
I can begin to observe what I had not previously observed and I can understand the grounded theory techniques better than before. I have started to draw out the steps and phases of the new research design with the current focus on the qualitative strand. I understand more now about categorical development and have outlined more questions I want to ask about the data as I proceed with recoding the data and continue to develop categories.
Aligned with my philosophical beliefs, I believe that there is a truth out there behind the process of the phenomenon of investigation but whether or not this real truth can occur only from coding and recoding for the context of my research is doubtful. But a mixed methods design perhaps could lead me closer to that ontological truth without actually reaching absolute truth. Aligned with my epistemological beliefs, the logical process (abductive) that underlies my use of grounded theory (develop hypotheses inductively from the data and use deductive methods to test the hypotheses against the data) aligns with my beliefs that knowledge is not certain and absolute. We need to continuously think about the data, think about what is happening in the data, think about how we interpret the data and how we know what we know to be true or perceive to be truth (meta-Philosophy) as long as everything is grounded in the data. All hypotheses, ideas, observations, and thoughts must be grounded in the data. We need to question our own biases and acknowledge them. All this while we maintain our sanity long enough to do so!
A big question that I have next is: when I have all the codes, and have developed all the categories and identified relationships between each category and the relevant properties and dimensions, what then? Grounded theorists talk about bringing everything together to form a theory whilst other grounded theorists discuss the idea of linking categories together to identify relationships in a process known as Axial Coding. I think I am currently leaning towards axial coding or some sort of coding technique that enables me to relate categories, because it is through the relation of categories and really understanding the way that categories interact with each other could I then begin to understand the way that the particular learning phenomenon of interest progresses from start to conclusion. This is challenging and whilst I shall try to work it all out for the sake of the diagrams I am drawing out as plans, the only way I think I am going to know for sure what I shall do is to simply do the coding. But the way I am viewing this at the moment is whilst the categories in themselves explain what is happening with certain parts of the phenomenon, by themselves they do not explain the process. There needs to be that extra step that identifies the process and the relationships therefore between elements of this process in order to better explain the phenomenon.
Once I have developed the ideas of the way I am going to approach the qualitative strand I shall then deal with the quantitative strand, fit everything within a mixed methods scenario if proven to be the most appropriate strategy, as well as a case study methodology if necessary, and then actually test my ideas against the data and remodify accordingly after receiving feedback from the supervisor.
‘till next time!
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!