A guide to writing Dissertation Findings and results

So, you’ve collected your survey data and conducted your interviews. Now you’re staring at a spreadsheet full of numbers and a transcript full of words, thinking, “How on earth do I put these together in one chapter?”

You’re not alone. Writing the Findings/Results chapter for a mixed-methods dissertation can feel like trying to solve a puzzle where the pieces are from two different boxes. But get it right, and it’s where your dissertation truly shines, revealing a rich, complete picture that neither method could achieve alone.

This guide will walk you through the process of presenting mixed-methods dissertation results in a way that is clear, compelling, and, most importantly, earns you marks. We’ll focus on how to integrate your data effectively and structure this crucial chapter.

Before you write a word, let’s be clear on the purpose. This chapter is primarily for presentation, not deep interpretation. Your job here is to lay out the key results from your quantitative data and the central findings from your qualitative data in a logical, organised way.

Think of yourself as a courtroom lawyer. You’re presenting the evidence—the stats, the quotes, the themes. You’re arranging it clearly for the jury (your marker) to see. The big argument about what it all means comes later, in your Discussion chapter. The key is to show, not tell, at this stage.

Your chapter shouldn’t feel like two separate reports clumsily stapled together. The most effective mixed-methods chapters are woven around your research questions.

Each sub-question acts as a natural hook to hang your data on. For example, if one of your questions was, “To what extent do students feel supported by university mental health services, and what are their main barriers to access?”, you can address this by:

1. Presenting the Quantitative Result: “Survey results indicated that only 35% of students felt ‘well-supported’ or ‘very well-supported’.”

2. Following up with the Qualitative Finding: “This statistical finding was illuminated by the interview data, which identified three key barriers: fear of stigma, long waiting times, and a lack of awareness about available services.”

See how that works? You’re using one method to illuminate the other, creating a natural flow.

Choosing a clear structure is 90% of the battle. Here are the two most common and effective ways to structure a Findings and Results chapter.

This is often the clearest way to start. You simply divide the chapter into two main parts before a final integration section.

• Part 1: Quantitative Results. Here, you present your stats. Be objective and factual. Use tables, charts, and graphs to display your data clearly.

• Part 2: Qualitative Findings. Here, you present your themes. Structure this section around the key themes that emerged from your interviews, focus groups, or content analysis.

Why it works: It’s logical, easy for the marker to follow, and ensures each methodology gets the dedicated space it deserves. The risk is that it can feel a bit disjointed if you don’t connect the two parts.

This is more advanced but creates a powerful, cohesive narrative. You structure the entire chapter around your research questions or overarching themes, and under each theme, you present both the quantitative and qualitative evidence that relates to it.

• Theme 1: Barriers to Access.

  • Quantitative Result: “65% of survey respondents cited ‘long waiting times’ as a significant or very significant barrier.”

  • Qualitative Finding: “This was echoed in the interviews, where participants described the waiting process as ‘frustrating’ and ‘disheartening’. Sarah, a second-year student, noted: ‘By the time my appointment came around, I felt like I’d already dealt with it alone, or it had gotten worse.’”

• Theme 2: The Role of Stigma.

  • Quantitative Result: “A weaker correlation was found between age and concern over stigma (r = .21, p<.05).”

  • Qualitative Finding: “However, the qualitative data provided nuance, suggesting that younger students were more concerned about peer judgement, while mature students feared it would impact their perceived professionalism.”

Why it works: This approach demonstrates true integration from the ground up. It answers the “so what?” of your data immediately and shows a deep understanding of how your two datasets speak to each other. It’s what markers love to see.

1. Start with an Introduction Roadmap

Begin the chapter by reminding the reader of your research questions and outlining the chapter’s structure. For example: “This chapter will present the integrated results of the study. It begins with an overview of the quantitative survey data, followed by a presentation of the key qualitative themes from the interviews. Finally, a summary table will be provided to illustrate the points of integration.”

2. Presenting Your Quantitative Data: The ‘Results’

• Be Objective: Report what you found, not what you think it means. Use phrases like “The data indicates…” or “The results show…”

• Visuals are Your Friend: Use clear, well-labelled tables and figures. Refer to them in the text (e.g., “As shown in Table 4.1…”). Don’t just plop a chart in and expect it to speak for itself.

• Highlight the Key Stats: Your reader doesn’t need every single number. Guide them to the most important and interesting results. If you did statistical tests, report the key values (like p-values) but explain them in simple terms.

3. Presenting Your Qualitative Data: The ‘Findings’

• Theme First: Start each section with the theme (e.g., “Theme 3: The Impact of Remote Learning”).

• Describe, then Illustrate: First, describe the theme in your own words. What is it about? Then, back it up with juicy, illustrative quotes from your participants.

• Anonymise: Use pseudonyms or participant codes (e.g., P1, P2).

• Weave Quotes In: Don’t just leave a quote hanging. Introduce it and then comment on it briefly. For example: “Several participants expressed a sense of isolation, which impacted their motivation. As one student, ‘Alex,’ poignantly stated: ‘It felt like I was just talking to my laptop all day…’ This sense of disconnection was a persistent challenge.”

4. The Magic Step: Integration and Weaving

This is the core of mixed methods. You need to explicitly state how the two datasets relate. Use phrases like:

• “The qualitative findings help to explain the quantitative results…”

• “While the survey provided a broad overview, the interviews added depth and context to these trends…”

• “Interestingly, the qualitative data revealed a nuance that the quantitative data did not capture…”

• Interpretation Overload: Save the “why” for the Discussion chapter. Here, just present the evidence and show how the two types connect.

• Data Dumping: Don’t feel you need to include every single statistic or quote. Be selective. Choose the results that are most relevant to your research questions.

• The “Island” Problem: Don’t leave your quantitative and qualitative sections as isolated islands. Build bridges between them with clear integration statements.

• Forgetting the Visuals: A well-designed table that summarises your key integration points can be a powerful way to end the chapter and provide a clear summary for the reader.

Ask yourself:

• Have I presented the data objectively, saving interpretation for the Discussion?

• Is my chapter structured logically around my research questions or themes?

• Have I used tables and figures effectively to present quantitative data?

• Are my qualitative findings supported by strong, illustrative quotes?

• Have I explicitly woven the datasets together, showing how they complement or contrast each other?

• Does the chapter tell a clear, coherent story that a reader can follow?

Writing a mixed-methods findings chapter is a challenge, but it’s also an incredible opportunity to showcase the strength of your research. By carefully integrating your data, you’re not just listing results—you’re building a compelling case. You’ve got this.

Dr. Eleanor Evans is a Senior Lecturer in Sociology and the Director of Undergraduate Dissertations at a leading UK university. She has over 15 years of experience helping students turn their ideas into successful research projects.