Mixed-Methods Research for Dissertation

Mixed-Methods Research for Dissertation

Mixed-methods research combines both qualitative and quantitative research approaches to provide a more comprehensive understanding of a research problem. This approach allows researchers to draw from the strengths of both methodologies, gaining a richer, more nuanced understanding of the phenomenon under investigation. In dissertation writing, mixed-methods research can be used to address complex research questions that require both statistical analysis and detailed, contextual understanding.

1. What is Mixed-Methods Research?

• Mixed-methods research involves collecting, analyzing, and integrating both quantitative (numerical) and qualitative (non-numerical) data within a single study. This approach provides a broader perspective on the research question by combining the strengths of both methods.

• The primary aim of mixed-methods research is to enrich the findings of each method, providing a fuller picture of the research problem.

2. Types of Mixed-Methods Designs

• Sequential Explanatory Design: Quantitative data is collected and analyzed first, followed by qualitative data collection and analysis to help explain or expand on the quantitative results.

  • Example: Conducting a survey to measure customer satisfaction with a product and then conducting interviews to explore why customers feel that way.

• Sequential Exploratory Design: Qualitative data is collected and analyzed first, followed by quantitative data collection to test or validate the qualitative findings.

  • Example: Interviewing a group of teachers to understand their perceptions of a new teaching method, followed by a survey to measure how widely those perceptions are shared.

• Concurrent Triangulation Design: Both qualitative and quantitative data are collected simultaneously, and the results are compared to check for consistency or contradictions.

  • Example: Running a survey to gather data on employee satisfaction and conducting focus groups at the same time to understand employees’ detailed experiences.

• Concurrent Embedded Design: Both qualitative and quantitative data are collected simultaneously, but one form of data is embedded within the other to address secondary research questions.

  • Example: Using quantitative surveys to measure the effectiveness of a program while embedding qualitative interviews to explore participants’ individual experiences.