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February 21, 2019

Update On The Ph.D Work, Part A: Literature Review

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!


October 14, 2018

Ph.D Update: Late September till 5th October

During the first couple of weeks of returning to my Ph.D. following a summer break, marking the fifth and final year of the Ph.D., I engaged with qualitative methodological literature and continued to develop my philosophical beliefs and methodological approach. After a couple of weeks of reading through appropriate chapters of qualitative methodological textbooks, I have been inspired and fascinated by the fact that I am better able to understand qualitative research concepts and contexts presented compared to three or four years ago. This awareness has enabled me to better explain and argue the relevance of qualitative research for my Ph.D. project and indeed for the general research context and type of data I am exploring. As ever, as always, there is always a lot more to say and what can be said, but I do believe I am at the point where I can produce methodological arguments regarding the relationship between qualitative concepts and the general research context. These ideas can only be further improved and developed as I continue to write the research design chapter.


What is interesting is my developing understanding has occurred not necessarily through constant rereading of the qualitative textbook literature, which can help, but through active engagement with the data, through testing out various methodologies and methods, and documenting their effectiveness and comparisons in their effectiveness and usefulness in exploring the phenomena of interest. Perhaps more specifically and importantly, what has impacted my understanding the most is the active engagement through coding and really exploring the data: breaking data down into segments and giving them meaning (codes) and being able to visualise links between these segments. This has really helped me to understand more what my data is about; to think about the nature and context of the data and its characteristics; to think about the way in which the data represents the phenomenon of interest, and, therefore, has assisted in developing my understanding of the relevance of qualitative methodologies particularly the approach I am developing. It’s not just about active data engagement: you have to be able to provide methodological and philosophical reasoning and justifications of your approach and it has to make logical and reasonable sense. This is what I am continuing to strive and achieve. Not an easy task by all means, it can take a long, long time, but it can happen and you can achieve. You just have to believe!


It is engaging with the data and the phenomenon at an embedded, detailed level that has assisted with that understanding of qualitative concepts and methodology. It is like an evolving relationship: you read the methodology textbooks, you actively engage with the code for a period, and that in turn increases your understanding of the methodological textbooks. Additionally, being actively engaged with the data increases your understanding of the data and the way in which the data represents the phenomenon of interest. I realised that my engagement with the data increased my understanding of the data and its representation, but finding out that it helped significantly in developing my understanding of qualitative textbooks is an interesting observation. It’s impossible to claim to know everything, that is not possible, but in the thesis I can detail the way in which engaging with the data has enabled me to better understand the purposes and objectives of qualitative data, and the way that I can argue that qualitative data could serve another purpose relative to the data and context of my research. Fascinating!

The key message to take away from this blog is, sometimes you just have to jump in and engage with the data. If it takes weeks or months to really understand the data as it has done with me, it doesn’t really matter. What matters is that you are able to return to the textbooks and be able to better understand the concepts of qualitative research and be able to begin to argue the concepts most relevant to your own research, whilst being able to argue which are not, and perhaps attempt to extend the scope and definitions of qualitative research.
It’s a journey, and it’s a journey of continuous improvement.


Keep going! You can get there! Believe in yourself and your capacity and capability to produce your thesis and promote your research!


October 06, 2018

The Fifth And Final Year Of The Ph.D.!

The fifth and final year of the Ph.D. is now underway! All plans lead towards the submission of the thesis next September, the VIVA defence a few weeks or months following the submission, and the production of more research papers. I have every desire to publish my work following the thesis and where possible, before the submission of the thesis. I have every desire as well to develop a book proposal and have this accepted by an academic publisher: I’m leaning towards the idea of converting my thesis into a book format. I have ideas of what I might like to cover.


I look forward to the coming year, a year that shall academically challenge, excite, scare, and push me and develop me further as an academic researcher. There is always much more to learn, but I am excited because after the many months of experimenting with different analytical approaches to the data, I feel that I am starting to put together a workable plan of data analysis. I feel excited because I can observe continuous development of my understanding of the phenomenon and the data that represents it. This has been achieved through continuous detailing and elaborating of my ontological and epistemological beliefs, and continuous elaborations of the way in which these link with the methodological approach and the methods of data analysis. As I begin to further develop my approach to analysing the data, these elaborations shall no doubt become more detailed and comprehensive.

But I also feel challenged and slightly nervous at the fact that this is the final year and I still feel like I have a lot of analytical work to do, even though I feel like I have already completed a significant amount. Another concern is the simple consideration of the workability of what I shall ultimately develop, and whether or not I’ll actually get the Ph.D. but those thoughts are probably common among a large number of people working towards their Ph.Ds. That said, I do feel more confident with the approaches that I am developing compared to what I was trying to achieve a couple of years ago and even a few months ago.

My understanding of my own epistemology and the way that my beliefs link with methodological approaches and the data analysis methods have altered over the years of thinking about them and experimenting with them. The significant time spent thinking about different philosophical orientations, methodological approaches and experimenting with different analytical methods have been beneficial. This is leading to a thesis chapter that shall include comparisons between different epistemological orientations, methodological concerns and data analysis methods, where they shall be critiqued and evaluated with regards to their effectiveness of exploring the particular type of data in relation to the research questions. It gives me the opportunity not only to write a thesis that provides new knowledge pertaining to the understanding of the phenomena, but also new knowledge with regards to methods and approaches that can be used to explore the phenomena represented as a particular type of text.

Despite these alterations there have been a couple of constants that have remained throughout the research so far: the idea that there is something real independent of our conceptions and beliefs about that something in the social world, and also the appreciation of and desire to adopt a coding and categorisation approach. Coding and categorisation of the data leads to the development of categories and themes, which can be used for further analysis depending on the aims and objectives of the research. Coding and categorising are considered to be the fundamental aspects of qualitative research, and can be a key element of mixed methods research. Qualitative research is dominated by text based resources of different forms and types, which, I am going to argue, can provide different types of knowledge and understanding of a phenomenon. Depending on one’s theoretical and philosophical orientation, one shall perceive the texts in different ways, and place different emphases and meanings upon the text in order to understand the text in various ways related to the phenomena in order to answer the research questions. Coding and categorising, as well as thematic analysing, the data is the key means of capturing the meaning of particular events, actions, and activities either implicitly or explicitly stated in the text. That is essentially qualitative research in a nutshell though, obviously, qualitative research is much more complex than that.

It is a journey, and it’s a journey of constant wonder, awe, inspiration, development, innovation and invention. It’s a journey of challenges, excitement, of emotion, of being inspired, of inspiring others, and it’s a journey that is unique to you and to you alone.

It has been an incredible journey, and it’s nowhere near finished yet! Sometimes I feel that I am really only just beginning: that a real “end” does not necessarily exist, therefore, this idea of “finishing” a Ph.D. is quite an interesting concept. What is it you are actually finishing? Are you finishing the Ph.D. research course? Yes, you are! But are you actually finishing your research? Is that it? Is it done? What about all the ideas that you have developed during the time on your Ph.D. that you had not had the time to implement or develop further? Or what was considered irrelevant at the time but you might be able to think of contexts where they are more relevant? Does your thesis really represent all that your research could be, has been, might be, and should be? You might complete the Ph.D. course, but in reality your own research has only just begun!

Thanks for reading!

‘Till next time!


September 05, 2018

Current State Of Play: Thesis Structure

I have altered the thesis structure several times relative to the research design. I have come to understand over the years that research design is not driven by the thesis: the thesis, its structure, its content and layout is guided by the research design. Quantitative, Mixed Methods and Qualitative research designs all influence the structure and ordering of the thesis in various ways.


I have thought about Mixed Methods and Qualitative theses given that I have been fascinated by both research designs. But now I am focussed on qualitative as the main component of the research, with quantitative analysis involved as deemed necessary, but as a smaller component that complements the qualitative.


It could almost be argued that in some way, quantitative data shall be embedded in a bigger qualitative project in order to provide a broader and more detailed picture of what is happening with the phenomenon of interest within the research context. I am not sure if this could be classed as mixed methods though. I would call it multi-method, because the collected data would serve both quantitative and qualitative and the quantitative analysis would be based on qualitative findings. Multi-method means multiple methods of, for example, data analysis used in the same methodological paradigm, in this case qualitative. It could still be a mixed methods approach but an embedded approach, but I shall have to think about this more. That said though, Mixed Methods is a continuously evolving methodological field with continuous potential for new contributions of creativity, innovation, possibility and lots of debates. Either way, the qualitative provides the framework within which the thesis is being developed, given that the qualitative side of the Ph.D. is considered the largest aspect.


Anyway, the the following thesis structure is now in place:


Introduction: this is going to be a chapter that shall be formally written last. This chapter shall simply introduce the research problem, research context, research issues, the need and value of the research, the research questions, research aims and objectives, research outcomes, and who the research is intending to benefit.


Literature Review, Setting The Scene: this chapter sets the scene and the key outcome of this chapter is to justify why a particular technological context is being used relative to the problems, questions etc. introduced in the introductory chapter. This involves evaluating and comparing each context relative to the phenomenon of interest. I am also attempting to engage with discussion and debate about terminology, and to provide my own definitions of different terms relative to the technological context, and attempt to address ambiguity and conflation.


Methodology Literature Review: this is a critical and analytical evaluation and comparison of different philosophies, theories, coding schemes, methodologies, and methods used to explore the phenomenon of interest within contexts very similar to the Ph.D. research. Additionally, the chapter shall report on the testing, evaluation, comparisons and critiques of different research methods in order to justify the most suitable approach to the research project. The actual approach used for the research project shall be described, explained, evaluated, critiqued and tested in the research design chapter.


Research Design: provides a full elaboration the research design phases including full details on the philosophies, methodology, methods and approaches that made up the design. The chapter shall also consist of design evaluations and shall comprehensively relate every part of the design to the research context, issues, problems, outcomes and questions. There shall also be a full discussion on the way in which the coding scheme and the themes were developed, tested, verified, clarified and validated.


Following the design there shall be chapters dedicated to discussing the coding scheme in more detail, as well as discussing identified categories and themes, and their interrelationships. Also as and where necessary there shall be chapters associated with thematic maps, and any quantitative analysis that takes place. It’s difficult to plan these chapters out though, because the chapter structure and content emerges from the data and not emerge from pre-existing theories and models. Hence, the structure and content of these later chapters are continuously emerging from the data analysis. There shall also be a chapter or a section of a chapter revolving around the application of theory in practice.


That’s the thesis at this time! Next are blog posts that cover a couple of the initial thesis chapters: the literature reviews.


April 08, 2018

Continuation of the Qualitative Thread: Current Thoughts on Axial Coding

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

Some Current Thoughts on the Qualitative Strand and Open Coding

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

Mixed Methods Research Design: Should This Now Be Considered Suitable?

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!


Research Design: A Reflection and Possible New Direction

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

Updated thinking about researcher influence on research design

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.


Summary


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

Methodological Breakthrough, Part B: Introducing The New Methodology!


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.


What next?


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?


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