If your dissertation is more explanatory, it will likely use quantitative methods. Quantitative methods tend to test a theory, or assess quantitatively the relationship between A and B. If you are doing exploratory research, this post will be more useful.
Here’s a suggested structure:
Okay, based on the provided structure for a qualitative dissertation, here’s a suggested structure for a quantitative dissertation using either a survey or experimental design. Note that word counts are suggestions and can be adjusted.
Chapter 1. Introduction (1.5K – 2K)
- Background to the Study: Provide context and relevant background information on the topic being investigated. Explain the societal or academic relevance of the research area.
- Problem Statement: Clearly articulate the specific problem or gap in knowledge that your research aims to address.
- Rationale for the Study: Explain why this research is important and timely. Highlight the potential contributions and significance of your study. It is common in to use statistics coming from industry to assess the importance of the topic.
- Research Aims and Objectives: Outline the broader aims of your research and the specific, measurable, achievable, relevant, and time-bound (SMART) objectives you will pursue to answer your research questions or test your hypotheses. (IMPORTANT: PLEASE NOTE YOU WILL KNOW THIS UNTIL YOU HAVE CONDUCTED A LITERATURE REVIEW – YOU MIGHT HAVE A STARTING IDEA BUT A REFINED AIM AND OBJECTIVES WILL COME UNTIL YOU READ THE LITERATURE).
- Significance of the Study: Discuss the potential theoretical and practical implications of your research findings. Who will benefit from this research?
- Structure of the Dissertation: Briefly outline the organisation of the remaining chapters.
Chapter 2. Literature Review (2K – 2.5K)
- Conceptual Framework: Define and discuss the key concepts and variables relevant to your research questions/hypotheses.
- Review of Existing Theories and Models: Explore relevant theories and models that provide a theoretical foundation for your study. Discuss how these theories relate to your research questions/hypotheses.
- Empirical Evidence: Critically review previous quantitative research (using surveys or experiments) that has investigated similar topics or variables. Identify what is already known and what gaps remain.
- Identifying Research Gaps: Based on your review of the literature, clearly identify the specific gaps in knowledge that your research will address. Explicitly link these gaps back to your research questions/hypotheses.
- Conceptual Framework and Justification for Variables and Measures: You will very likely develop a conceptual framework that you will test. You will here set up hypotheses that you will test. You can also explain why you have chosen specific variables to investigate and justify the methods used to measure them based on prior research and theoretical considerations.
Chapter 3. Methodology (1.5K -2K)
- Research Philosophy: Discuss the underlying philosophical assumptions guiding your research (e.g., Positivism, Post-positivism). Explain how this philosophy aligns with your research approach and the nature of quantitative inquiry.
- Research Design: Clearly describe the chosen research design (e.g., cross-sectional survey, longitudinal survey, between-subjects experiment, within-subjects experiment, quasi-experiment). Justify why this design is appropriate for addressing your research questions/hypotheses and discuss its strengths and limitations.
- Participants/Sample:
- Recruitment Strategy: Explain how participants were recruited (e.g., random sampling, convenience sampling, stratified sampling).
- Sample Size: Justify your chosen sample size, potentially including power analysis considerations. If you are doing undergraduate or master’s dissertations, sometimes your University will prescribe a set number of participants (80-100).
- Participant Characteristics: Describe the key demographic or other relevant characteristics of your sample.
- Data Collection Instruments:
- Surveys: If using a survey, describe the questionnaire in detail, including the types of questions (e.g., Likert scale, multiple-choice), the constructs being measured, and the reliability and validity of the instrument (if established). Include a copy of the survey in an appendix.
- Experiments: If using an experiment, describe the experimental procedures in detail, including the independent and dependent variables, the experimental conditions, any manipulation checks, and the materials used.
- Pilot Study (if applicable): Describe any pilot testing conducted to refine your instruments or procedures.
- Data Collection Procedures: Outline the step-by-step process of how the data were collected (e.g., online survey administration, in-person interviews with structured questionnaires, laboratory experiment).
- Data Analysis Techniques: Clearly specify the statistical techniques that will be used to analyse the data (e.g., descriptive statistics, t-tests, ANOVA, correlation, regression, structural equation modeling). Justify the choice of these techniques in relation to your research questions/hypotheses and the nature of your data.
- Ethical Considerations: Discuss the ethical considerations addressed in your research, including informed consent, anonymity, confidentiality, data security, and any ethical approvals obtained.
Chapter 4. Results (2K – 3K)
- Descriptive Statistics: Present descriptive statistics for your key variables (e.g., means, standard deviations, frequencies). Use tables and figures to summarize the data clearly and concisely.
- Inferential Statistics: Present the results of your inferential statistical analyses in a logical order, typically following your research questions or hypotheses.
- For each research question/hypothesis, state the hypothesis (if applicable), describe the statistical test used, report the test statistic, p-value, degrees of freedom (where relevant), and the direction and strength of the effect (if any).
- Use tables and figures effectively to present the statistical findings. Ensure that tables and figures are clearly labeled and referenced in the text.
- Avoid interpreting the results in this chapter; focus on presenting the statistical findings objectively.
Chapter 5. Discussion (1.5K -2K)
- Summary of Findings: Briefly summarize the key findings from the results chapter in relation to your research questions/hypotheses.
- Interpretation of Findings: Interpret the statistical results in the context of your research questions/hypotheses and the existing literature reviewed in Chapter 2.
- Discuss whether your findings support or contradict previous research and theoretical predictions.
- Explain any unexpected or non-significant findings and offer potential explanations.
- Theoretical Implications: Discuss the theoretical contributions of your study. How do your findings advance or challenge existing theories or models?
- Practical Implications: Discuss the practical implications of your findings for relevant stakeholders (e.g., practitioners, policymakers, organizations). How can your findings be applied in real-world settings?
- Strengths and Limitations of the Study: Critically evaluate the strengths and limitations of your research design, methodology, and findings. Acknowledge any potential biases or limitations that may have influenced the results.
Chapter 6. Conclusion (1.5K – 2K)
- Restatement of Research Aims and Objectives: Briefly reiterate the main aims and objectives of your research.
- Summary of Key Findings and Contributions: Provide a concise summary of the most important findings and their overall contribution to the field.
- Meeting the Research Objectives/Answering Research Questions: Explicitly state whether and how your research objectives were met and your research questions were answered (or hypotheses were supported/rejected).
- Theoretical and Practical Contributions (revisited): Briefly reiterate the key theoretical and practical contributions of your study.
- Limitations (revisited): Briefly summarize the main limitations of your research.
- Suggestions for Future Research: Based on your findings and limitations, suggest potential avenues for future research in this area. What questions remain unanswered? What could be investigated further?
Important Considerations for Quantitative Dissertations
- Clarity and Precision: Quantitative research emphasises clarity and precision in defining variables, formulating hypotheses, and reporting statistical results.
- Statistical Rigor: Ensure that your chosen statistical methods are appropriate for your research questions and data, and that you report the results accurately and completely.
- Objectivity: Maintain an objective stance when presenting and interpreting your findings, avoiding personal biases.
- Visual Aids: Use and figures effectively to present quantitative data in a clear and understandable manner.
- Appendices: Include relevant supplementary materials in appendices, such as survey instruments, experimental protocols, ethical approval documents, and detailed statistical output (if not included in the main body).