Areas for future research

Grey Gneiss

There comes a time in drawing together the conclusions of any piece of research, whether it is a long PhD study or a shorter project, when there is a realisation that there is SO much more to do. This is not necessarily a bad thing, although a novice researcher might consider it a sign of weakness. Every single study has its own set of limitations on the level of accuracy, comprehensiveness, and study conditions. In the normal course of events, the research team need to consider carefully these possible limitations, then attempt to minimise or eradicate them, or perhaps just simply acknowledge the limitations and explain their concerns. It is much, much better to be able to recognise the limitations and try to reduce them, than to blissfully (and mistakenly) soldier onwards as if there are no limitations whatsoever.

Normally, towards the end of the concluding chapter of a dissertation, it is wise to include a short section which identifies “opportunities for further research”. This only needs to be three pages long, because longer might suggests that there are too many things unknown about the study (and one short paragraph might suggest that there is nothing more to find out – which will be interpreted as either arrogance or ignorance, and either way is bad). A common term which is used in this context is that our own research has been “built on the shoulders of giants” which implies that we are able to see further or in more detail, not simply because we are more intelligent, or have better vision, but because we have benefitted from the work of the people who have explored these issues before us.

This section analysing further research opportunities brings into sharp focus three important aspects of the PhD award. Firstly, it helps to make clear the new contribution of the researcher towards a better understanding of this research topic and the discipline as a whole. Remember, making “an original contribution to the subject knowledge” is one of the two key requirements of a PhD (the other being to demonstrate that it is the student’s own work). Secondly, this section of the dissertation identifies other possible research projects which can build upon the present study. It might be to recommend an extension of the study – more participants, a wider geographical area, more samples analysed etc. – or it might refer to various offshoot projects on tangential ideas which were revealed during the present study but the researcher did not have the time (or the money, opportunity, equipment etc.) to undertake at the time. This is useful because it help to demonstrate that the researcher is aware of these possible research directions (and potential limitations to the current study) rather than blindingly missing obvious avenues to explore in the future which might provide a greater depth of knowledge on this topic. Thirdly, in identifying potentially fruitful areas for further research, the researcher is helping to place the current dissertation in the context of the bigger picture of ongoing work on this topic. It is effectively offering this PhD dissertation as another “shoulder” on which future researchers can build upon to gain a better understanding of this subject area. It is effectively adding another level onto the foundations of earlier research.

So, for a brief flash of time, the student is a world-leader in this particular research topic, a state-of-the-art expert in the why, wherefore, and significance of this very specific research question – only to be eclipsed by the next upcoming researcher who will take this a stage further. A good reason to celebrate and enjoy the celebrity while it lasts!

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Going beyond

Wrong way

Perhaps surprisingly to most novice researchers, a research degree does not need to provide “the complete answer” to a problematic question, only to demonstrate the competence of the researcher in their ability to conduct a systematic investigation and to “make an original contribution” to the disciplinary area. Getting an “answer” might be a nice way to demonstrate some added-value, but more than likely the results of the research will only clarify a small area of interest, and will probably raise a whole lot of new questions which require to be investigated. An essential aspect of presenting and interpreting the results of a PhD or Masters project is to show clearly what is known about the specific topic at the start of your research, and what can be added to the sum or knowledge by the time your research is concluded. This “original contribution” might be quite small, and it could appear in a variety of ways, such as a new method of experimentation, or more detailed results than previously, or simply being able to contrast and compare with prior studies to accentuate the similarities and differences which allow us to form a clearer image of the ‘big picture’. All the same, there needs to be something new which is contributed to the subject by the research, even if it is only to be able to verify previous ideas from an enlarged sample or from a different angle. Simply reviewing the existing state of knowledge on the subject, or repeating exactly a previous study, will not generally qualify for a doctorate on its own. There needs to be a clearer demonstration that the sum of knowledge is being advanced.

 

This is what I call the “So what?” stage.

 

The student has progressed step-by-step through the research project, following the usual stages that have been identified between the student and the supervisor(s) and is now lining up for a big finale. There will be good documentation provided on the nature of the research problem, a critical review of existing academic literature, a detailed explanation of the methodology used in the study, ways of gathering and analysing new data, and an extensive section presenting the results of the study. This has taken a lot of work to produce the dissertation to this stage. So what? What does all this this mean? Why does it matter?

To answer these questions, the researcher needs to show that the study has been based on the quality work of previous researchers, but has now gone beyond this, even only in a modest way. The result should have something new and significant to say about this research topic. This is perilous ground, because the research student needs to show that they have extended the pool of knowledge, but not gone so far out on a limb that the conclusions are hard to justify and support. Partly it is about having confidence in the revelations uncovered by the study (and the researcher’s interpretation of these) and partly it is about not being too cocky about what the results really mean in the great scheme of things. Yes, there are PhD’s which dramatically change the course of the discipline by careering off in a completely new direction, but these are quite rare, and most research can be shown to be a clever and intuitive progression on existing research which pushes just a little further. The research methods and the resultant conclusions need to be based on the evidence collected, and needs to be defendable. All studies have limitations, so these need to be acknowledged and shown how they have been minimised. Don’t claim to have found the alchemist’s stone just because it looks like the results might be heading in that direction. It is much better to keep the claims modest and stoutly defendable, rather than stretch the imagination (and the credibility) of the readers without being able to provide the required evidence to substantiate the claims or conclusions.

Interpreting the data

building

Building on existing knowledge

A key role of any supervisor is helping the research student to bridge the gap between the fundamentals about what is currently known about the research topic, and the new results which have been generated through the research activities of the student. All research is built upon some level of pre-existing knowledge on the subject, even if existing knowledge is patchy or otherwise insubstantial. In the literature review chapter, the student will have built up the profile on what is already known about the research topic and how that information can be backed-up by evidence from the academic literature available. In the analysis chapter, the first task is to provide some interpretation for the new, primary research conducted by the student, but a significant secondary task is to relate this back to the previously discussed evidence and underpinning theories which were explained in the earlier chapter(s). This can be a tricky task because the new research results might either fully support earlier work (in which case, what’s new about the research?) or else directly contradict it (in which case how do you prove the superiority of the new results?).

It is a useful tip to bear in mind that hindsight is a wonderful perspective, so try to avoid feeling too smug about the wonderful flashes of insight produced by the new research. Always assume (unless proven otherwise beyond doubt) that the earlier researchers did the best job that they could with the information, equipment, and currency of information at the time they were doing their research. It is easy to look back in history and wonder why our predecessors could ever have believed some of the accepted wisdom and “common sense” of the time, but in fact we are no different: we simply have much more information in a greater level of detail, but it would be a fool or a knave who would claim to know every last thing about the chosen subject. In most circumstances the research will both tweak prior definitions, and then throw clearer light on an existing area or understanding, or it will provide new data to enable the researcher to propose a new way of thinking about the existing data and justifying that new approach by producing new evidence (or a new way of interpreting the existing evidence).

Either way, the first stage of research analysis is to compare the new information with what has already been understood, and then go beyond this to open up a new area that is worthy of further research (and/or a proposing a different way of understanding the subject). Two common failings at this stage of the research process are either to appear to present the conclusions as if nothing important had ever preceded the current research (thereby inventing a whole new branch of epistemology) or else failing to restrict the conclusions to the actual results of the current research and instead attempting to make grand conclusions for the whole of the discipline (rather than just for the current research project). Either way, getting to grips to understand the importance of the new research, and using it to build upon earlier research results to improve our knowledge of the subject, is a fundamental step in the dissertation.

Establishing the storyline

Contents

One of the first things that both the supervisors and the research students need to remember is that although the dissertation is the justification of an academic thesis, it also needs to tell a good and convincing story. There is little point in making a wonderful discovery if you cannot properly communicate with other people to tell them about it. Research is about discovering something unknown, and like any good mystery story, there needs to be an introduction to set the scene for your readers, (the literature review) there needs to be a storyline to develop the research agenda (starting with the methodology) there need to be clues discovered as the story develops (the results chapter(s)) and there needs to be a moment of final revelation of the object of your search (the analysis and conclusions).

The delivery of this story requires a certain writing style – it needs to follow the academic conventions of the subject discipline, it is not a novel – but that should not mean that the ‘story’ that the researcher wants to tell should not be easy to read. There are some simple tips, such as to first lay-out using numbered sub-headings, the main headlines in the ‘story’. The separate sections can then be written under these headings and linked together to form the chapters. A good idea is to begin by drafting the contents page of the dissertation, listing the chapter headings (1. Literature Review, 2. Methodology… etc.) and then entering the various headings of likely sub-sections. In addition to helping to establish a coherent storyline (which can be amended as the writing progresses) this enables the dissertation to be written in a manner which is not necessarily linear (sub-sections can be skipped and returned to a later date) and built up piece-by-piece while still keeping within the framework of the story. It is also a good tool for discussions between the research student and the supervisor about stage-by-stage progress (I have used this with red (not-done) green (completed) and amber (working on it) highlights, to help students prioritise what bits of writing need to be tackled next).

The bottom line is that the research student needs to craft a good story to introduce, explain, and discuss their research project, and if this is easy to read, then it will be easier for readers to follow and perhaps build-upon in subsequent activities. This includes correct spelling, good grammar, and simple tactics such as to avoid l-o-n-g and cumbersome sentences (I had once student who wrote a sentence containing the word ‘and’ seven times! This really was three separate sentences and would have been far easier to understand if it had been written in a simpler style.) Another avoidable error is to include sentences which give ambiguous comments. If there is a way in which your comments can be misinterpreted, it is human nature that someone will take the wrong meaning, and this can be easily avoided by actually saying what you really mean, and keeping this in simple language that cannot be misunderstood. Using hierarchical numbering for the chapters, sections, and sub-sections not only helps to create a clear storyline, it also helps to allow cross-reference to earlier (or future) comments in the dissertation.

It is the role of the research supervisor to read and give comments to help improve the direction of the writing process. The student does not need to like these comments (and indeed, at their own risk, may chose to ignore them) but they should heed them because it is the duty of the supervisor to direct the work of the student to ensure that they give the very best presentation possible of their work for examination and further scrutiny.

How to Illustrate your results

Diagrams

When I was writing up my own PhD (in the antediluvian days before personal computers, desktop publishing software, or graphics packages!) I was given a very useful lesson by the Prof. who was my supervisor. I was agonising about how good my hand-drawn graphs and maps needed to be, how precise the individual, hand-printed, iron-on lettering needed to look. He informed me, rather drily, for that was his preferred style, that I was “… training to be a geologist, not a draughtsman!

From that response I understood, correctly, that if my diagrams are clear and accurate enough to convey my key point(s) then a point of diminishing returns is quickly reached on the time spent labouring over them. There is no need to produce a “work of art” – it is about “communication”. The situation is slightly different now, for there are lots of clever software packages, in Excel and elsewhere, which can quickly produce lots of impressive diagrams which can be “cut-and-pasted” into the text with minimal effort – but the two fundamental points remain the same. Firstly, if the initial data is weak and/or disorganised, then any resulting illustration is hardly worth the effort of trying to interpret with any degree of real meaning. As computer programmers are taught early – GIGO – (Garbage in, garbage out)! Secondly, a diagram (or a map, or a graph) needs to convey something meaningful. It is a visual expression of something that the author is trying to convey to the reader, so if this can be communicated clearly and simply, that is sufficient. There are far too many elaborate diagrams that are over-designed, and the result can appear so complicated that it is the diagram, rather than the results, that needs to be explained to the reader.

In some subjects, there are more-or-less standard conventions for diagrammatic representations, such as histograms, bar-charts, tolerance diagrams, or pie-charts. It usually makes sense to abide by these conventions because it can help comparison with similar studies elsewhere. Usually, simple is best. Let the eloquence of the diagram communicate the data for you. Sometimes, particularly due to the speed and ease with which computer-generated diagrams can be generated, there can be a tendency to “graph every variable against every other variable” in the hope that a stunning correlation is unexpected revealed. While this can happen, it is more likely that simply a blinding flash of the obvious is revealed, without contributing anything more than confusion to the current understanding of the topic. As with the use of statistics, it is always better if the author actually understands what they are trying to do before attempting the activity. It is too easy to drop into the text a “pretty photograph” or a diagram of a rather obvious feature without actually conveying much real information (e.g. a pie-chart of the male/female split of respondents; it is probably better just to give the percentage figures).

In a few cases, the use of a few clever diagrams, such as fishnet images of topography, or bar-chart information superimposed on a map to show geographical abundance, can produce a stunningly visual interpretation, but these should be used sparingly. While it is true that a (good) picture can say a thousand words, the tokenistic use of photographs, diagrams, or graphs can simply clutter up the main text, and require further text to explain the image to the reader. A good illustration actually says something clearly and makes a positive contribution to help the reader understand the accompanying text and data.

Using statistics in research

calculator

For me, the golden, unbreakable rule is, never use any statistics if you do not really understand what they mean! This might seem obvious, but it is surprising how frequently statistics get misused or misinterpreted to support an argument that actually has no real basis in fact. The famous saying that there are three types of lies – “lies, damned lies, and statistics” is attributed to Prime Minister Disraeli, but when properly used, statistics can be clear, unequivocal, and very supportive in communicating complex data simply. The main problem(s) are often started by people deliberately selecting the information that they want to hear and then seeking for statistical back-up which looks impressive and difficult to challenge. Secondary problems occur when people either do not properly understand what the real statistics are saying, or when people choose to deliberately select or twist the statistical information which seems to support their preferred point of view. Ultimately, all three problem areas both devalue the use of statistics and also take us even further away from a clearer understanding of the situation that we are trying to interpret and communicate.

A good “rule of thumb” is to stick to the simplest means of statistically expressing the results that you want to communicate. Percentages, pie-charts, and histograms might look fairly unadventurous if you are trying to impress an examiner, but they have the advantage that they are quick to produce, clear to interpret, and easy to understand. Fancy calculations may look more impressive, but they are frequently harder to produce, more difficult to fully understand, and have a greater chance of either the creator or the reader making errors of interpretation. A common error is to quote percentages rather than give simple numerical values for small population samples. If 7 out of 12 of your interviewees agree, say “7 out of 12 agree that…” rather than “58.33%…” A difference of 1 person immediately gives an 8% error and is clumsier. Keeping it simple gives both a truer impression of the data and an easier comparison with other results. Similarly, I have seen some very impressive and complex diagrams, complete with 3-D shading and vector trends, which actually do not tell us very much at all because the detail is lost in the artistic flamboyance. They look fancy but add nothing to the discussion.

Quite often, certain disciplinary areas will have their own conventions as to which statistical procedures are common, or preferred, and how they are presented. The supervisors should be able to advise on these common standards, and the benefit is usually that the new research data can both make use of earlier research results, and can be easily contrasted and compared with already published data in the discipline. Some statistical procedures can look complicated to calculate, but are actually quite straightforward to use. All universities will have opportunities for research students to attend courses on statistical methods which are appropriate for different subject areas of research, so students should get training early in the research to avoid any subsequent false starts. There are lots of self-guide short courses on the web, and of course in text-books, but self-tuition is also open to misunderstanding, so it is always best, in the first exploration at least, to work through the procedure(s) alongside someone who is already very familiar with the statistical technique(s). Bear in mind, contrary to some current political rhetoric, there are no “alternative facts” simply facts that you acknowledge and facts that you might prefer to ignore. Research is about improving knowledge, not picking just the bits that you like.

Timing and deadlines

Clock

As the student gets towards the end stages of creating the dissertation, it might seem odd to return to the issues of timing and deadlines, but there has never been a more crucial period to study the demands of time. Many students go right to the wire with the time taken to produce a completed thesis for submission, indeed a great number of students go beyond their deadlines and end up trying to juggle the completion of their research with the demands of a new job. That can be a very difficult situation and is to be avoided if at all possible. In some cases the deadlines will be self-determined, so there may be no harm done if they slip a little. In many situations, however, there is a formal limit to the student’s registration, so missing this deadline could prove disastrous. Normally, the students and the main supervisor need to indicate to the Graduate School of the university about three months in advance, that the student is preparing to submit the dissertation manuscript on a certain date. This is to enable the university to set the wheels in motion to select internal and external examiners, to check their suitability, and to arrange the administrative details for the viva event. Up until this point, most work “deadlines” were convenient milestones which were self-imposed to provide guidance and structure. The final submission date is a real deadline, and needs to be treated seriously. It makes sense to work back from this agreed date-of-submission, and plan the last few months of the PhD research like a military campaign.

Firstly, although getting the dissertation printed and loosely-bound should only take a few hours, do not leave it to the last minute, because if anything unexpectedly goes wrong (e.g. the printer breaks) then the carefully choreographed timetable is shattered. Similarly, do not underestimate how long it will really take to get the exact wording for the final analytical chapter and conclusions, or the inevitable few weeks that will need to be spent ‘snagging’ the final text. Apart from a final double-check on spelling and grammar, the captions of any illustrations will need to be cross-checked, as well as making sure that the page numbering corresponds to the contents pages and that every reference cited in the text has been itemised correctly in the reference list at the end. Insufficient attention to the details of spelling and referencing is often what makes the difference between a clear pass and “minor revisions required”. All this will take more time than an optimistic student expects! It is critical that some ‘redundancy time’ is built-in to any work plan in order to provide some slack for the likelihood of delays, deliberations, and minor disasters. The student will have spent so long in direct contact with the text that sometimes even the most obvious errors and omissions are not picked up until the very last moment. Five or six months before the anticipated submission date, sit down the supervisory team and set a schedule of ‘soft’ (desirable) and ‘hard’ (i.e. not moveable) deadlines to punctuate a work-plan leading to the final submission of the manuscript. Be realistic, then stick to the plan and do not get side-tracked with interesting but fruitless tangents which distract from the goals.

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