Methodology
Methodology At A Glance
The methodology of a study is the most technical aspect of doing a dissertation. During the coursework phase of your doctorate, you will likely take courses on both qualitative and quantitative methodology and analysis. Within each methodological paradigm, there are a number of common research designs that are frequently used in doctoral research:​
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Qualitative: Case Study, Phenomenology, Grounded Theory, Qualitative Descriptive, Ethnography​
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Quantitative: Experimental, Quasi-Experimental, Causal-Comparative, Correlation, Ex-Post Facto ​
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Mixed Methods: Sequential, Convergent, Parallel
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During the topic development phase of the dissertation, you will need to determine which research design is best suited to shedding light on the research gap you identified. Once you make that determination, the purpose of the methodology chapter is to write, essentially, an academic recipe for carrying out your study. ​ Key elements you will need to address in your Chapter 3 or methodology section are:
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Research Design Justification​
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Data Collection Procedures
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Sampling Technique
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Participants and Inclusion Criteria
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Data Analysis Methods
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Validity and Reliability (for quant studies)
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Trustworthiness (for qual studies)
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How will Dissertation Demystified help me?
Dissertation Demystified's methodology module is designed to help you design a feasible yet impactful study. Although we teach you the most important aspects of the various research designs listed above, the goal of this module is practical rather than academic or theoretical.
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Informed by research in open science and open data, we coach in considering how to design a study that is accessible and makes a real world impact. We also ensure that you are set up for success when you go to collect your data (whether it be secondary data, surveys, or interviews with participants). A common pitfall many doctoral candidates encounter is designing a study for which they cannot obtain data:
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For a quant study, it is important to consider if validated instrumentation or secondary data exists to operationalize your study's variables. Some doctorate candidates think they will design their own instrument, but survey development and validation is the work of a separate dissertation on its own!
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For a qual study, it is important to consider if you can actually get in contact and recruit the participants you are interested in. A common misstep is to propose interviewing executives or individuals high up in an organization and not being able to contact them.