Using Mixed Methods in Dissertation Research

Using Mixed Methods in Dissertation Research

Mixed methods research combines both qualitative and quantitative research techniques, allowing you to capitalize on the strengths of both approaches. Here’s how to use mixed methods in your dissertation:

1. What Is Mixed Methods Research?

• Definition: Mixed methods research involves collecting, analyzing, and integrating both qualitative and quantitative data within a single study. This approach allows for a fuller, more nuanced understanding of a research problem.

• Benefits: Mixed methods can offer a more comprehensive view of your research topic by providing both numerical evidence (quantitative) and in-depth insights (qualitative). It’s ideal when the research problem cannot be fully understood using only one type of data.

2. How to Design Mixed Methods Research

• Sequential Explanatory Design: In this design, you start with quantitative data collection and analysis, followed by qualitative data to explain or interpret the quantitative findings. This is useful when you have large-scale data and want to further explore or validate the results with qualitative data.

  • Example: Conduct a survey to gather numerical data on public attitudes toward climate change, followed by interviews with participants to understand the reasons behind their views.

• Sequential Exploratory Design: This approach begins with qualitative data collection, followed by quantitative data to test or generalize the qualitative findings. It’s often used when exploring new areas with qualitative research and later quantifying the findings.

  • Example: Use interviews to explore patient experiences with a healthcare service, then use a questionnaire to measure how prevalent those experiences are among a larger population.

• Concurrent Triangulation Design: In this approach, both qualitative and quantitative data are collected simultaneously, and the results are compared or integrated to provide a comprehensive analysis. This design is useful for corroborating or cross-validating findings from different data sources.

  • Example: Administer a survey while also conducting interviews with the same group of participants, then compare and analyze both sets of data together.

3. Data Collection and Integration

• Collecting Both Types of Data: In mixed methods, data collection can be done in parallel or sequentially. You may start with a survey (quantitative), then follow up with interviews or focus groups (qualitative), or you can gather both types of data at the same time using different methods.

• Integration: After collecting the data, you need to integrate the findings. This might involve comparing and contrasting quantitative results with qualitative insights or using one set of data to clarify or validate the other.

4. When to Use Mixed Methods

• Complex Research Problems: Use mixed methods when your research question requires both numerical data to identify trends and qualitative data to understand the reasons behind those trends.

• Validation or Enrichment: Mixed methods can help validate quantitative results with qualitative insights or enrich qualitative findings with broader generalizable data.