Reporting and discussing your findings

This page deals with the central part of the thesis, where you present the data that forms the basis of your investigation, shaped by the way you have thought about it. In other words, you tell your readers the story that has emerged from your findings. The form of your chapters should be consistent with this story and its components.

Contents:

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.

Finding your focus

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:


Tip

…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.

What have you learnt from your data?

The first step is to clarify for yourself 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 you try these techniques:

Activity

1. 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.)

2. 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?

3. Use these groups and headings to make a plan of the points you want to make in your discussion.

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 definition

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.

Activity

1. Write about your data for 5 minutes. You don't have to show what you write to anyone.

2. Stop.

3. 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.

Three kinds of story: macrostructures for a thesis

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 hypothesis story (this is the standard framework for theses in the empirical sciences)
    • state your hypotheses
    • test them
    • discuss the implications
  • the analytic story (a common framework for theses in the social sciences)
    • What are the key concepts you have used in this study?
    • How do your 'findings' shed light on these concepts and, through them, on the substantive topics you studied?
    • What, therefore, has become of your original research problem and the literature regarding it?
  • the mystery story
    • starts from empirical examples
    • develops the questions by discussing them
    • gradually leads the reader to interpretations of the material and to more general implications of the results.

The big picture

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

in order to make clear your contribution to knowledge in the field.

Present your findings

This page and the next, on reporting and discussing your findings, deal with the core of the thesis. 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, shaped by the way you have thought about it. In a thesis including publication, it will be the central section of an article.

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.

Every thesis writer has to present and discuss the results of their inquiry. In these pages we consider these two activities separately, while recognising that in many kinds of thesis they will be integrated. This section is concerned with presenting the analysis of the results of data analysis.

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.

Structure

Each chapter needs an introduction outlining its organisation.

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.

After that, the organisation will vary according to the kind of research being reported. Below are some important principles for reporting experimental, quantitative (survey) and qualitative studies.

What to include

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

Reporting conventions differ according to whether the data involved is quantitative or qualitative.

Quantitative data

The purpose of the results section of the thesis is to report the findings of your research. 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).

Data commentary element example

Instructions: Click on the highlighted data elements in the example 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.

Activity: Data commentary element example

Instructions: Click on the text below to identify the location element, summary and highlighting statement.

The influents to filter A and B were analysed fully on a number of occasions, and the averaged results are presented in Table 6.1. It can be seen from the table that the wastewaters from plants A and B and of similar composition.

Sometimes a reduced location element is used which gives only the table or figure number in brackets after the highlighting statement.

Examples:

  1. The ranges of metal atom concentrations for the two precipitate types were found to overlap (Table 6)
  2. 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 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 archeological 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 here to the specific results you have presented.

Past or present tense?

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.


Qualitative data

The reporting of qualitative data is much less bound by convention than that of quantitative data. The data itself usually consists of words, from written documents or interview transcripts (but may include images), which have been analysed in some way, often into themes. 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 through the layers of detail 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'.

Click on the highlighted text below to read the comments.

Example from a Doctor of Education thesis:

6.4.3 Themes from the Interview Data

In analysing the interview data, two themes emerged which will be discussed in this section. These themes were: the complexity and challenges of working with families and the professional satisfaction and challenges of program planning for children in preschool or childcare.

For each of these graduates, their work with children was clearly the area of their professional lives that was bringing the most satisfaction, although there were some challenges identified. In the interviews, the data reveal that they were all seeking ways to improve their pedagogy and achieving success in different ways

Angela suggested that in her second year of teaching she had changed in that she was programming in a "more child oriented" way. She discussed this change:

One of the things I've changed is this idea of herding children through the Kinder day: they go from indoor play to snack time to the mat and so on. How I do it now is that I have a lot of different things happening at once. I'll have a small group on the mat and there might be some children sitting down and having a snack and there's still some children in home corner playing.

These comments seem to provide evidence that Angela is growing professionally for two reasons. First, the ability to identify changes in her program suggests to me that she has deeper pedagogical knowledge gained through critical reflection on her practice, and second, there is congruence between her expressed beliefs and the practice she describes.



Discuss your findings

In the discussion of your findings you have an opportunity to develop the story you found in the data, making 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 expect some interpretation of the findings that makes these connections.

Research question

In your discussion you must draw together your research question and your own research results. If the discussion is in a self-contained chapter or section you will 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?

Relation to other research

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.
  • In presenting your own interpretation of the results, consider the strengths and weaknesses of alternative interpretations from the literature.

Implications

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

Writing your discussion

The skill in writing a successful discussion is in moving backwards and forwards between others' research and your own research, making it clear:

  • which has been done by other people
  • which has been done by you
  • and how they complement each other.


Tip

Remember that you are dealing with three different issues and the three must be clearly differentiated for the reader.

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...

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:

1. Indicate the degree of probability (note how the claim progressively weakens):

It is certain that

It is very probable/ highly likely that

It is likely that

It is possible that

It is unlikely that

reducing fat intake lowers the risk of heart disease.

Reducing fat intake lowers the risk of heart disease.

Reducing fat intake could/might lower the risk of heart disease.

Reducing fat intake may lower the risk of heart disease.

2.Distance yourself a) from the claim:

Reducing fat intake appears to lower the risk of heart disease.

It seems that reducing fat intake lowers the risk of heart disease.

Some researchers suggest that reducing fat intake lowers the risk of heart disease.

or b) from the data, by showing its limitations:

Some studies indicate that reducing fat intake lowers the risk of heart disease.

For this age group , reducing fat intake lowers the risk of heart disease.

In most of the cases studied , reducing fat intake lowered the risk of heart disease.

3. Use a qualifying verb:

Reducing fat intake tends to lower the risk of heart disease.

Reducing fat intake contributes to lowering the risk of heart disease.

4. In practice, a combination of these methods is often used:

The majority of studies indicate that for this age group, reducing fat intake contributes to lowering the risk of heart disease.

References

Evans, D., & Gruba, P. (2002). How to Write a Better Thesis (2nd ed.). Parkville: Melbourne University Press.

Golden-Biddle, K., & Locke, K. (1997). Composing Qualitative Research. Thousand Oaks: Sage Publications.

Silverman, D. (2005). Doing Qualitative Research: A Practical Handbook (2nd ed.). London: Sage Publications.

Swales, J.M., & Feak, C.B. (2004). Academic Writing for Graduate Students (2nd ed.). Ann Arbor: University of Michigan Press