So there is something I keep stumbling over when reviewing journal articles or other SoTL writing. Besides a general lack of methodology, if methodology is actually addressed it often misses the point. But I struggled with explaining this in an accessible way. I might have figured it out, bear with me:
Theory, Methodology, Method
Theory: Ideally when undertaking an educational inquiry (research) in the methodology section you would speak about your worldview. Under which premise you are going to look at your research? Are you coming from a position of wanting to explore or test an entity, assumed reality, phenomenon; or are you wanting to understand how people (learners) experience or think about a specific phenomenon, entity, process, situation? You might come across words such as positivism and interpretivism. There are no right or wrong perspectives here. It’s all about becoming aware of the lenses through which you want to look, and what might help you to design your project.
A really nice article explaining all these elements in 5 pages is this:
Alharahsheh, H., & Pius, A. (2020). A review of key paradigms: Positivism VS interpretivism. Global Academic Journal of Humanities and Social Sciences, 2(3), 39-43.
Methodology is the research design. Your approach to your research (inquiry). What are you going to explore. Why? How are you going to go about it? Why? How are you going to analyse the data? Why this way? Are there other options?
How they are connected: You might want to employ a theoretical framework to scaffold your project. Theories are a good way to build a structure around a project. They can be a useful lens through which to look at your project and your data.
For instance you might find many educators subscribing to social constructivism as a theoretical framework. This will influence your research design (methodology) and subsequently the choice of research methods–the tools with which we do the actual data collection. But it doesn’t stop there. The methods will influence the type of data you can gather, and what that data is and is not able to tell you.
Procedural versus Qualifying Justification
Less confident design does not have a methodology section, it goes straight from research question to methods.
Simplified Example:
We wanted to find out how well the students adapted to the flipped classroom approach* we used last year. So we decided to send the students a questionnaire.
Or the rationale does not explore how the methods relate to the methodology.
Simplified Example:
We wanted to find out how well the students adapted to the flipped classroom approach we used last year. So we decided to send the students a questionnaire as this is a cohort of 120 students and this is the best way to reach them.
Unanswered questions:
- What kind of data are these methods expected to produce?
- How would this answer the research question?
I call these justifications procedural. They can focus on issues such as ease of access to the method or the participants, or a quick cull of literature that provides the strengths for a method, but does not explain how this data is expected to answer the research questions. While elements of these discussions are useful. Only focussing on these procedural justifications can lead to problems with the findings, such as not having the right type of data to address the research question, or not having sufficient data to produce a convincing case.
Simplified Example:
We wanted to find out how well the students adapted to the flipped classroom approach we used last year. So we decided to send the students a questionnaire as this is a cohort of 120 students and this is the best way to reach them. Questionnaires are a good way to reach larger numbers of participants and enable us to establish patterns and interrelationships of various aspects. Only 34 students ended up answering the questionnaire and the answers do not provide a conclusive pattern.
A more in depth engagement with methodology would have established that return rate of less than 50% is typical, and other forms of data collection would have offered the opportunity to gather further evidence, and potentially undertake data triangulation.
More confident designs provide what I call qualifying justifications for their methodology and provide a succinct logical narrative from research questions, (via theory), methodology, methods, data, to data analysis. They explore how the method and the type of expected data fit into the narrative of the project. What kind of things I expect to be able to answer, and what I think might not be addressed in this situation. This is the purpose of the methodology part. It builds the bridge between the literature and your (eventual) data.
Summary
- Be conscientious in formulating your research question.
- From what theoretical perspective are you going to explore?
- What have others done?
- What research design are you choosing?
- Why?
- What methods belong to this design?
- What type of data do you expect?
- How is this going to help you answer your questions?
- What issues might you expect?
- What is your plan when problems occur?
*This is not a real life example, just the first thing that popped into my mind.
Glassick provided a useful set of questions to navigate the planning of your project: Glassick’s.pdf (evms.edu)
Nathalie Tasler, PhD, SFHEA, MPhil, PGDip CCM, PGCert LTHE 
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