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The reporting and discussion thesis chapters deal with the central part of the thesis. This is where you present the data that forms the basis of your investigation, shaped by the way you have interpreted it and developed your argument or theories about it. In other words, you tell your readers the research story that has emerged from your findings. These chapters will form the bulk of your complete thesis. Before you even begin writing up the reporting and discussion chapters, you’ll need to undertake some thinking and planning.
Find the story in your data
For many kinds of research, the main work of interpretation cannot be done until most of the data has been collected and analysed. For others, the data already exists (in the form of archival documents or literary texts, for example) and the work of interpreting it begins much earlier in the research process.
Whatever kind of research you are doing, there comes a moment when your head is full of ideas that have emerged from your analysis. Ideally, you will have written them down as they came to you. Now you have to convert that mass of material and ideas into a written text that will make sense to a reader, and do justice to your findings.
How will you decide which aspects of your findings are the most interesting and important? It is useful to remind yourself what the task of writing up research is all about:
…the major task of writing [about our research] involves working out how to make contextually grounded theoretical points that are viewed as a contribution by the relevant professional community of readers.
(Golden-Biddle & Locke, 1997, p. 20)
That is, in your thesis you need to make points that are:
contextually grounded (based on your data)
theoretical (related to relevant theory)
viewed as a contribution by the relevant professional community of readers (they add something to the current body of research or theory).
These points must fit into a framework that makes a coherent story of your findings.
The first step is to clarify what you know now, as a result of your research. David Evans and Paul Gruba (2002, p.112) remind us that our minds continue to work on problems when we aren't thinking about them consciously. So it is worth finding out what conclusions your brain has reached while you were collecting and analysing your data. Evans and Gruba suggest trying these techniques:
Write down all the things you know now that you didn't know when you started the research. Use a single sentence for each item. (At this point, don't worry about whether they relate to your aims or research questions.)
Sort the sentences into groups. Give each group a heading. Now check the headings against your research question(s). Do all the headings relate to the research question(s)? Do the questions need refining?
Use these groups and headings to make a plan of the points you want to make in your discussion.
Freewriting
Making lists works well for some people, but not for others. Another technique you can use to unlock your unconscious thought processes is freewriting.
Freewriting on a topic means taking a fresh piece of paper or opening a new word-processor document and writing anything that comes into your head on that topic for a limited time. It must be in whole sentences and you must not stop. If you have nothing to write, write 'I have nothing to write'. This is writing to think. It probably won’t produce text you can use in your thesis, but it might help to clarify your ideas and show you ways to structure your argument.
Try freewriting using the guideline below:
Write about your data for 5 minutes. You don't have to show what you write to anyone.
Stop.
Now read over what you've written. Have you learnt anything? Is there anything there you want to develop further? You could try highlighting key words, or identifying any points that need further investigation.
The way you present the analysis and interpretation of your data sits within a wider thesis framework, which can itself be thought of as a story (adapted from Silverman, 2005, p. 242-43).
The challenge for every thesis writer is to hold the detail of the data in focus without losing sight of the big picture of the research. This is why reporting data analysis is not enough. You need to:
establish the connections between the patterns that emerge from your analysis and your research questions
relate those connections to the existing research and theory.
This will make clear your contribution to knowledge in the field.
Present your findings
Every thesis writer has to present and discuss the results of their inquiry. In a traditional doctoral thesis, this will consist of a number of chapters where you present the data that forms the basis of your investigation, along with your analysis and interpretation of the data.
For some fields of study, the presentation and discussion of findings follows established conventions; for others, the researcher’s argument determines the structure. Therefore it is important for you to investigate the conventions of your own discipline, by looking at journal articles and theses.
There is a great deal of disciplinary variation in the presentation of findings. For example, a thesis in oral history and one in marketing may both use interview data that has been collected and analysed in similar ways, but the way the results of this analysis are presented will be very different because the questions they are trying to answer are different. The presentation of results from experimental studies will be different again. In all cases, though, the presentation should have a logical organisation that reflects:
the aims or research question(s) of the project, including any hypotheses that have been tested
the research methods and theoretical framework that have been outlined earlier in the thesis.
You are not simply describing the data. You need to make connections, and make apparent your reasons for saying that data should be interpreted in one way rather than another.
Each chapter needs an introduction outlining its organisation. This signposts how the data will be presented.
Examples
Chemical Engineering PhD thesis
In this Chapter, all the experimental results from the phenomenological experiments outlined in Section 5.2 are presented and examined in detail. The effects of the major operating variables on the performance of the pilot filters are explained, and various implications for design are discussed. The new data may be found in Appendix C.
Literature PhD thesis
The principal goal of the vernacular adaptor of a Latin saint's life was to edify and instruct his audience. In this chapter I shall try to show to what extent our texts conform to vernacular conventions of a well-told story of a saint, and in what ways they had to modify their originals to do so, attempting also to identify some of the individual characteristics of the three poems.
The organisation of your reporting and discussion chapter(s) will vary according to the kind of research being reported. Below are some important principles for reporting experimental, quantitative (survey) and qualitative studies.
The results of experiments are almost always presented separately from the discussion.
Present results in tables, graphs and figures or other appropriate visual representations.
Clearly label and number tables, graphs, figures or other visual representations.
Use text to introduce tables and figures and guide the reader through key results.
Point out differences and relationships, and provide information about them.
Include negative results (then try to explain them in the Discussion section/chapter).
There are generally accepted guidelines for presenting the results of statistical analyses of data about populations or groups of people, plants or animals. It is important that the results be presented in an informative way.
Demographic data that describe the sample are usually presented first.
Remind the reader of the research question being addressed, or the hypothesis being tested.
State which differences are significant.
Highlight the important trends and differences/comparisons.
Indicate whether the hypothesis is supported or not.
The presentation and discussion of qualitative data are often combined.
Qualitative data is difficult to present neatly in tables and figures. It is usually expressed in words, and this results in a large quantity of written material, through which you must guide your reader.
Structure is therefore very important.
Try to make your sections and subsections reflect the themes that have emerged from your analysis of the data, and to make sure your reader knows how these themes evolved. Headings and subheadings, as well as directions to the reader, are forms of signposting you can use to make these chapters easy to navigate.
You can read more about reporting qualitative results in the next section, Reporting conventions.
For all types of research, decisions about what data to include are important.
Include what you need to support the points you need to make. Be guided by your research questions(s) and the nature of your data.
Make your selection criteria explicit.
More detail can be provided in an appendix. Evans and Gruba (2002) offer some good advice: 'Include enough data in an appendix to show how you collected it, what form it took, and how you treated it in the process of condensing it for presentation in the results chapter.' (p. 105)
Reporting conventions differ according to whether the data involved is quantitative or qualitative. When you are dealing with quantitative data, you usually present the data you obtained in appropriate figures (diagrams, graphs, tables and photographs) and you then comment on this data.
Comments on figures and tables (data commentary) usually have the following elements:
a location element
a summary of the information presented in the figure
a highlighting statement to point out what is significant in all the data presented (eg trends, patterns, results that stand out).
Reading the following excerpt in the table below which explains the function of the sentences used in this paragraph. Then identify the elements in the activity below.
Table 5 shows the most common modes of computer infection in Australian businesses. As can be seen in the table, home disks are the most frequent source of infection.
Location element
Table 5
Summary
most common modes of computer infection in Australian businesses
Highlighting statement
home disks are the most frequent source of infection
Sometimes a reduced location element is used which gives only the table or figure number in brackets after the highlighting statement.
Examples:
The ranges of metal atom concentrations for the two precipitate types were found to overlap (Table 6)
Quantitative analysis revealed some variation in the composition of the rods in the various exservice samples (Figure 7 and Table 5).
Commentary on results may include:
explanations
comparisons between results
comments on whether the results are expected or unexpected
comments about unsatisfactory data.
Dealing with "Problems"
The sentences in the table below are typical of explanations for problems in the data that may need to be explained. It is possible to mix and match the different elements of each sentence to create a new sentence that more accurately explains a problem in your own data.
The difference between expected and obtained results
may be due to
the incorrect calibration of the instruments.
This discrepancy
can be attributed to
the small sample size.
The anomaly in the observations
can probably be accounted for
by a defect in the camera.
The lack of statistical significance
is probably a consequence of
weaknesses in the experimental design.
The difficulty in dating this archaeological site
would seem to stem from
the limited amount of organic material available.
Adapted from Swales & Feak, 2004, p. 138
If you are discussing your findings in a separate chapter or section, limit your comments to the specific results you have presented.
Past or present tense?
What is the appropriate tense to describe data? The table below indicates the accepted tenses for reporting data commentary elements.
Location element
present tense
…the averaged results are presented in Table 6.1.
Table 5 shows…
Summary of procedure
past tense
The influents to filter A and B were analysed fully on a number of occasions,…
Results of analysis
past tense
The ranges of metal atom concentrations … were found to overlap.
Comments
present tense
This discrepancy can be attributed to the small sample size.
The reporting of qualitative data is much less bound by convention than that of quantitative data. The data itself usually consists of words (quotes) from written documents or interview transcripts, which have been analysed in some way, often thematically categorised. Qualitative data may also be multimodal and include images, video or sound. In reporting the data, it is generally important to convey both the themes and some of the flavour of the actual words.
The data needs to be connected back to the overarching research question it relates to. This can be done through the introductions to carefully-structured sections and subsections. Individual data extracts can be connected back into this structure through a process of 'tell-show-tell'.
Discuss your findings
In the discussion of your findings you have an opportunity to develop the story you found in the data, drawing connections between the results of your analysis and existing theory and research. While the amount of discussion required in a thesis may vary according to discipline, all disciplines require some interpretation of the findings that draw these connections. There are three key elements to incorporate into this discussion: links to your research question; relation to other research; and implications of your research.
In your discussion you must draw together your research question and your own research results - this is your opportunity to demonstrate how your research results relate to your research question(s). If the discussion is in a self-contained chapter or section you’ll need to briefly summarise the major findings that come from the research and relate them to what you originally proposed to find out.
If your research is testing a hypothesis, you need to answer these questions:
Do your research findings support your initial hypothesis? Why and how?
Do your findings only support the hypothesis in part? Why and how?
Do your findings disprove your hypothesis? Why and how?
What else do your findings tell you, over and above what you initially set out to investigate?
Since one of the requirements of a doctorate is to make a contribution to knowledge, it is essential to show how your results fit in with other work that has been done in your field.
Point out the agreements and disagreements between your data and that of others.
Highlight any new knowledge that your research contributes to the field of study.
In presenting your own interpretation of the results, consider the strengths and weaknesses of alternative interpretations from the literature.
Differentiating your research
The skill in writing a successful discussion is in integrating others' research with your own research, making it clear:
which research has been done by other people
which research has been done by you
and how they complement each other.
Some techniques to differentiate your own research from previous research in your writing (these are suggestions, not rules, and your best guide is to see how other writers in your discipline do this):
Use the first person to describe your findings.
My data shows...
Consistently use ‘this’ to refer to your own research and refer to previous research by name, place or time.
This study...
The findings of this research...
Smith and Geva found that...
A previous study in Belgrade...
Make reference to similarities or differences in approach or findings.
Similar research carried out in the 1980s showed that...
Use the present perfect tense to highlight the recent relevance of your research in comparison with earlier research, referring to it in the simple past.
This study has shown a prevalence rate of 2.5 which is greater than that found by Smith and Geva in their Belgrade study...
Another aspect of making clear the contribution of your research is to draw out the implications of your findings. Depending on the nature or your research, these will probably be related to:
current theory
technical applications
professional practice.
Using cautious language
Discussing results and drawing conclusions involves making claims about interpretation, significance and applicability. This is done within a research tradition where existing knowledge is always being modified in the light of new results. As a researcher, you are expected to distinguish carefully between:
knowledge you are sure of because you have reliable evidence for it
other knowledge you are less sure of
other knowledge you think is only within the realms of possibility.
Therefore, very strong claims, like the one below, are rare in academic writing.
Reducing fat intake lowers the risk of heart disease.
A claim like this, which implies that the statement is true in every case, cannot be supported with evidence. Claims should therefore be specific and precise, and the level of certainty must match the level of evidence. There are many methods used in academic writing to qualify a claim:
