Tag Archives: PhD

Checking references and citations


It is amazing how many students get into a muddle over the simple process of ensuring accurate links to the supporting evidence for their claims. Let us get this right; it is not the supervisors job to check that citations and references are correct, but the External Examiner of the degree certainly will check this. For that reason, it is the supervisor’s job to make sure that the research student gets it right. It is not a difficult task, but it can be time-consuming, so the task needs meticulous care.

To lay down some ground rules, when researchers make a claim or a statement of ‘fact’ in their writing, we need to establish the source of that claim. There are two ways to do this; either the information is new, i.e. as a result of the new research, or it is derived from previous research. When it is the latter, the normal way to credit the source of the evidence is to include a citation in the statement, (such as, “There are …. (Rennie and Smyth, 2019)” or “Rennie and Smyth (2019) claimed….” This then flags the full reference, listed in alphabetical order at the end of the document, which in this case is, “Rennie, F. and Smyth, K. (2019) Digital Learning: The Key Concepts. London: Routledge”. (I also usually include the ISBN – International Standard Book Number – for books, and the DOI – Digital Object Identifier – for journal articles, but that is just me being extra-sure that subsequent readers can locate the item.) Crucially, if a claim or a ‘fact’ is given without a citation to the supporting evidence, then it is assumed that the information source is the writer. If it is not the writer, then the missing citation is regarded either as shoddy workmanship at best, or plagiarism at worst. Plagiarism – knowingly misrepresenting some other persons direct words/ideas as your own – is regarded a major misdeed in academia, so an important role of the supervisor is to ensure from an early stage that the student treats accurate referencing very seriously.

I encourage my students to adopt the same rigor that I do, which is, firstly, start to compile the list of references right from the very start of the research project. Always write out the references in full, and do not leave any information out – the chances are that you will forget to go back to correct it. When I find new relevant articles, books, or other resources that I know I want to include in my writing, I add the references to the master list as I read them. Secondly, when I have completed my final draft text (and usually a couple of times before then) I sit down with a printout of the main text on one side, and the list of references on the other. I go through the main text, marking with a highlighting pen every citation that I come across. I then turn to the list of references and highlight it there too. By the time that I have read the whole of the text, every citation should be highlighted, and every reference should also be highlighted. If I have missed any references, or included references that I have not actually mentioned in my text, then this is the opportunity to update the reference list by either adding or removing the relevant items. It is a laborious process, but it is fool proof.

The danger of not doing this is when a particular citation catches the eye of the External Examiner, and they turn to the reference list for the full details. If the reference is missing, they do not know whether the writer has made a one-off mistake, or if there are many more missing references. The result is an almost mandatory viva condition to “Check all references” before passing the dissertation, rather than getting a “no corrections required”.


Conclusions and recommendations

QuestionsFor a PhD, indeed for most academic research, the researcher is judged more on the quality and justification of the research method, rather than getting “the answer”, but the interpretation of the results, the conclusions, and any possible recommendations are a pretty important part of the outcome too. There are three common mistakes made by early career researchers for which supervisors must be on the lookout, but basically they all revolve around the one question – do the conclusions relate directly to the evidence produced by the research?

This might seem a rather obvious question, but it is important to address first. Frequently the writer of the conclusions will have very weak, generic conclusions that seem to fade out and say nothing. Sometimes it seems that an experienced researcher could write these sort of conclusions before even starting the research – they lack clarity and don’t really say very much. Secondly, is the opposite extreme, the temptation to read too much into the data and make conclusions or predictions for which there is no real evidence. This is almost worse than understating the results, for a critical reader would begin to wonder if the whole of the research project had been influenced by this optimistic speculation. It would certainly make me re-read the data analysis more carefully to see if the researcher displays any suggestion that they “knew the results of the research” in advance, and looked favourably on the data in order to “find” the answers that they wanted. In this phase of the research, the supervisor has a crucial role as a critical friend, to challenge the research student into justifying their conclusions, and relating this directly back to the evidence displayed by the analysis of the data.

The third common error in writing the research conclusions is that the writer describes very plausible conclusions, which actually have little or nothing to do with the research project that has been undertaken. The researcher has become so immersed in the research that s/he has lost a sense of the boundaries of the project. Everything seems to be connected to everything else, and there is a lack of focus on what is really relevant, or evidence-led.

In my role as a supervisor, I call this “the so-what?” moment. The student has designed a research project, identified a key question and related it to the current knowledge of the subject, then gathered a load of new primary data which has been analysed to reveal some “results”. So what? What does this actually mean? Sometimes the results show what can not be proved, and this can be almost as important as getting “an answer”. Knowing what the evidence does not show, or where there are blind-alleys in the data gathering, can be critical in the design of a new research project that advances our knowledge a stage further. What do the results really say? What claims can be based on the research and what does it tell us about the research question that is an original contribution to the subject?

In this respect, the advice from a supervisor needs to be offered carefully, in order not to discourage or demoralise the student, for this is a time for honest self-reflection. It is better to be slightly less ambitious in the research aims but be more robust in the collection and interpretation of data, rather than strive for an idealistic but very ambitious research aim that is undermined by careless data collection, too many assumptions instead of hard evidence, and joining the dots to make speculative predictions rather than making comments based on solid evidence that can be justified by the data. I always tell research students to take a pause after they have written the penultimate draft of their data interpretation chapter, then go back to the very start of the dissertation; read every section afresh, as if for the first time, and make the final tweaks to the narrative. Then, fresh with this knowledge of where they are and how they got there, try to write the conclusions by answering the “so what?” question.

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!

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 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


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


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.