In longer pieces of work, these chapters are usually separate. Information contained in this section will highlight the finer details of writing up your findings and discussion sections. We will use the model of Description — Analysis — Synthesis, which are typically the three components readers expect to see in these two sections.
Preparing to write By the time you're ready to write up your findings, we assume that you've already completed the analysis of your findings. By now, you should know what you are going to write about. We also assume that you have used some sort of software program to help you with the organisation of your findings. If you have not completed this process, you must do so before beginning to write. If not, your findings chapter may end up a confusing and unorganised mess of random information.
If you need help in this area, make sure to seek it out before beginning to put your findings down on paper.
One of the main issues that students tend to encounter when writing up their findings is the amount of data to include.
By the end of the research process, you've probably collected very large amounts of data. Not all of this can possibly appear in your dissertation without completely overwhelming the reader.
As a result, you need to be able to make smart decisions about what to include and what to leave out. One of the easiest ways to approach this task is to create an outline. In approaching the outline, it is in your best interest to focus on two key points. Firstly, you need to focus on answering your research questions. Secondly, you must include any particularly interesting findings that have cropped up as you completed your research.
An outline will give you the structure you need, and should make the whole process of presenting your findings easier. We realise that it is going to be a difficult process to pick and choose pieces of data to include. But you must be diligent in the work that you cut out. A findings chapter that is long and confusing is going to put the reader off reading the rest of your work.
Introducing your findings The findings chapter is likely to comprise the majority of your paper. This is a huge chunk of information, so it's essential that it is clearly organised and that the reader knows what is supposed to be happening. One of the ways you can achieve this is through a logical and organised introduction.
There are four main components that your introduction should include: Reminding the reader of what you set out to do A brief description of how you intend approaching the write up of the results Placing the research in context Letting the reader know where they can find the research instruments i.
You probably love watching films that keep you on your toes. They gradually build suspense, then surprise you with a dramatic plot twist just when you thought you'd sussed the story line. Well, your findings chapter is sort of like a really lame movie script. With a findings chapter, there should be no suspense for the reader. You need to tell them what they need to know right from the beginning. This way, they'll have a clear idea about what is still to come.
A good introduction will start by telling the reader where you have come from in the research process and what the outcome was in a couple of paragraphs or less. You need to highlight the structure of the chapter as you generally will do with all chapters and where the reader might find any further information e. Organisation of data So, you have created an outline for your findings and highlighted what you thought was most interesting or important for your project. Now you need to consider how you might present these findings in the most logical way to the reader.
This is really going to depend on the type of project you have created. For example, if you have completed a qualitative research project, you might have identified some key themes within the software program you used to organise your data. In this case, highlighting these themes in your findings chapter may be the most appropriate way to proceed. Not only are you using information that you have already documented, you are telling a story in each of your sections which can be useful in qualitative research.
But what if you undertook a more quantitative type study? You might be better off structuring your findings chapter in relation to your research questions or your hypotheses. This assumes, of course, that you have more than one research question or hypothesis. Otherwise you would end up just having one really long section.
This brings us to our next student mistake — trying to do too much within one section. Subheadings are ultimately going to be your friend throughout your dissertation writing. Not only do they organise your information into logical pieces, they give the reader guidelines for where your research might be going.
This is also a break for the reader. Looking at pages and pages of text without any breaks can be daunting and overwhelming for a reader. You don't want to overwhelm someone who is going to mark your work and who is responsible for your success or failure.
When writing your introduction, be clear, organised and methodical. Tell the reader what they need to know and try to organise the information in a way that makes the most sense to you and your project. If in doubt, discuss this with your supervisor before you start writing. Presentation of qualitative data Qualitative data largely encompass longer and more detailed responses. If you have conducted things like interviews or observations, you are likely to have transcripts that encompass pages and pages of work.
Putting this all together cohesively within one chapter can be particularly challenging. This is true for two reasons. Secondly, unlike quantitative data, it can often be difficult to represent qualitative data through figures and tables, so condensing the information into a visual representation is simply not possible.
As a writer, it is important to address both these challenges. When considering how to present your qualitative data, it may be helpful to begin with the initial outline you have created and the one described above. Within each of your subsections, you are going to have themes or headings that represent impactful talking points that you want to focus on.
If you have used multiple different instruments to collect data e. This is so that you can demonstrate to more well-rounded perspective of the points you are trying to make. Once you have your examples firmly selected for each subsection, you want to ensure that you are including enough information. You must set up the examples you have chosen in a clear and coherent way. Students often make the mistake of including quotations without any other information.
Usually this means writing about the example both before and after. This was a focal point for 7 of my 12 participants, and examples of their responses included: [insert example] by participant 3 and [insert example] by participant 9. The reoccurring focus by participants on the need for more teachers demonstrates [insert critical thought here].
By embedding your examples in the context, you are essentially highlighting to the reader what you want them to remember. Aside from determining what to include, the presentation of such data is also essential. Participants, when speaking in an interview might not do so in a linear way.
Instead they might jump from one thought to another and might go off topic here and there. So the quotes need to be paired down to incorporate enough information for the reader to be able to understand, while removing the excess. Finding this balance can be challenging. You have likely worked with the data for a long time and so it might make sense to you. Try to see your writing through the eyes of someone else, which should help you write more clearly. Presentation of quantitative data Presentation of quantitative data can be equally as challenging as the presentation of qualitative data, but for very different reasons.
For example, with the qualitative data you might be concerned about length. Quantitative data poses the risk of overwhelming the reader with numbers, statistics, and percentages that can make heads spin with confusion. Something to consider first with numeric data is that presentation style depends what department you are submitting to. In the hard sciences, there is likely an expectation of heavy numeric input and corresponding statistics to accompany the findings.
In the arts and humanities, however, such a detailed analysis might not be as common. Therefore as you write out your quantitative findings, take your audience into consideration.
Just like with the qualitative data, you must ensure that your data is appropriately organised. Again, you've likely used a software program to run your statistical analysis, and you have an outline and subheadings where you can focus your findings. There are many software programs available and it is important that you have used one that is most relevant to your field of study. For some, Microsoft Excel may be sufficient for basic analysis.
Whatever program you have used, make sure that you document what you have done and the variables that have affected your analysis. One common mistake found in student writing is the presentation of the statistical analysis. During your analysis of the data, you are likely to have run multiple different analyses from regressions to correlations. Often, we see students presenting multiple different statistical analyses without any real understanding of what the tests mean.
Presentation of quantitative data is more than just about numbers and tables. You could also explain how they relate to the research question. However, depending on how you have organised your work, this might end up in the discussion section. Students who are not confident with statistical analysis often have a tendency to revert back to their secondary school mathematics skills.
They commonly document the mean, median, and mode for all of their results. Now, these three outcomes can be important. But having a good understanding of why you are proceeding with this strategy of analysis is going to be essential in a primarily quantitative study.
That noted, there are different expectations for an undergraduate dissertation and a PhD thesis, so knowing what these expectations are can be really helpful before you begin. Presentation of graphs, tables, and figures Thanks to modern technology, making graphs and figures to correspond to your work needn't be a tedious and time-consuming task. What criteria did you use to select material e. Quantitative methods example The survey consisted of 5 multiple-choice questions and 10 questions that the respondents had to answer with a 7-point Likert scale.
The aim was to conduct the survey with customers of Company X on the company premises in The Hague from July between and A customer was defined as a person who had purchased a product from Company X on the day of questioning. Participants were given 5 minutes to fill in the survey anonymously, and customers responded. Because not all surveys were fully completed, survey results were included in the analysis. Qualitative methods Describe where, when and how the interviews were conducted.
How many people took part? What form did the interviews take structured, semi-structured, unstructured? How long were the interviews and how were they recorded? Participant observation Describe where, when and how you conducted the observation.
What group or community did you observe and how did you gain access to them? How long did you spend conducting the research and where was it located? How did you record your data e. Existing data Explain how you selected case study materials such as texts or images for the focus of your analysis. What type of materials did you analyze? How did you collect and select them? Qualitative methods example In order to gain a better insight into the possibilities for improvement of the product range, semi-structured interviews were conducted with 8 returning customers from the main target group of Company X.
A returning customer was defined as someone who usually bought products at least twice a week from Company X. The surveys were used to select participants who belonged to the target group years old. Interviews were conducted in a small office next to the cash register, and lasted approximately 20 minutes each. Answers were recorded by note-taking, and seven interviews were also filmed with consent. One interviewee preferred not to be filmed. What is your plagiarism score?
Compare your paper with over 60 billion web pages and 30 million publications. Quantitative methods In quantitative research, your analysis will be based on numbers. In the methods section you might include: How you prepared the data before analyzing it e. The dataset was checked for missing data and outliers. The data was then analyzed using statistical software SPSS. Qualitative methods In qualitative research, your analysis will be based on language, images and observations.
Methods might include: Content analysis : categorizing and discussing the meaning of words, phrases and sentences Thematic analysis : coding and closely examining the data to identify broad themes and patterns Narrative analysis: looking at storytelling structures and tropes and interpreting their meaning Discourse analysis : studying communication and meaning in relation to their social context Qualitative methods example The interviews were transcribed and thematic analysis was conducted.
This involved coding all the data before identifying and reviewing six key themes. Step 4: Evaluate and justify your methodological choices Your methodology should make the case for why you chose these particular methods, especially if you did not take the most standard approach to your topic.
Discuss why other methods were not suitable for your objectives, and show how this approach contributes new knowledge or understanding. You can acknowledge limitations or weaknesses in the approach you chose, but justify why these were outweighed by the strengths.Information contained in this section will highlight the finer details of writing up your findings and discussion sections. Tell the reader what they need to know and try to organise the information in a way that makes the most sense to you and your project. Did you conduct surveys by phone, mail, online or in person, and how long did participants have to respond? Usually this means writing about the example both before and after. Like any other chapter in your thesis, an introduction is an essential component of your discussion. This brings us to our next student mistake — trying to do too much within one section.
It will affect the mark that you obtain on your overall dissertation. Why is this the most suitable approach to answering your research questions? Existing data Explain how you selected case study materials such as texts or images for the focus of your analysis. Usually this means writing about the example both before and after. Let's think about your outline and subheadings. Preparing to write By the time you're ready to write up your findings, we assume that you've already completed the analysis of your findings.
In a pie chart, you might show one section as purple and the other as green.
Many students choose to contact professional editors to help with this as they hold the relevant expertise to guide you on the correct path to creating a perfect discussion section that is ready for submission. Something to consider first with numeric data is that presentation style depends what department you are submitting to. It needs to demonstrate how you have attempted to answer your research questions. You need to ensure that you have clearly identified data that relates to your research questions, hypotheses, or themes of your study. If you chose to structure your findings by theme, it might make sense to continue this into the analysis chapter. But you still have the opportunity to demonstrate how you have met that coveted gap in the research and generally made a useful contribution to knowledge.
Subheadings are ultimately going to be your friend throughout your dissertation writing. What type of materials did you analyze? For much of your academic career, you've likely been asked to use research to justify a position that has already been set. Finding this balance can be challenging. If you have conducted things like interviews or observations, you are likely to have transcripts that encompass pages and pages of work.
The final mistake we see is the duplication of writing or absence of writing when presenting a graph. You need to tell them what they need to know right from the beginning. Secondly, unlike quantitative data, it can often be difficult to represent qualitative data through figures and tables, so condensing the information into a visual representation is simply not possible. We tell students about critical thinking and the importance of it on a daily basis. By the end of the research process, you've probably collected very large amounts of data. Presentation of quantitative data is more than just about numbers and tables.