A Note on Multimethodology
Methods is a word that has gained importance in much scientific research. There are countless books on scientific method within a variety of subjects.
“Method, mode, way imply a manner in which a thing is done or in which it happens. Method refers to a settled kind of procedure, usually according to a definite, established, logical, or systematic plan: the open-hearth method of making steel; one method of solving a problem.” (dictionary.com)
“The process of the scientific method involves making conjectures (hypotheses), deriving predictions from them as logical consequences, and then carrying out experiments or empirical observations based on those predictions. A hypothesis is a conjecture, based on knowledge obtained while seeking answers to the question.” (wikipedia.com)
It is a plan and logical procedure, yet it is one that changes. Shifting interactions, or shifty — full of doubt according to others.
Quantitative and qualitative research can be seen as loosely coupled systems, where of open systems interacting.
Often when discussing these one can hear the mention of multi and mixed methods research.
“Mixed methods research is more specific in that it includes the mixing of qualitative and quantitative data, methods, methodologies, and/or paradigms in a research study or set of related studies. One could argue that mixed methods research is a special case of multimethod research. Another applicable, but less often used label, for multi or mixed research is methodological pluralism.” (wikipedia.com)
It is possible to somewhat divide these, and one attempt to do so is into:
- Quantitatively driven approaches/designs in which the research study is, at its core, a quantitative study with qualitative data/method added to supplement and improve the quantitative study by providing an added value and deeper, wider, and fuller or more complex answers to research questions.
- Qualitatively driven approaches/designs in which the research study is, at its core, a qualitative study with quantitative data/method added to supplement and improve the qualitative study by providing an added value and deeper, wider, and fuller or more complex answers to research questions; qualitative quality criteria are emphasised but high quality quantitative data also must be collected and analysed.
- Interactive or equal status designs in which the research study equally emphasizes (interactively and through integration) quantitative and qualitative data, methods, methodologies, and paradigms. This third design is often done through the use of a team composed of an expert in quantitative research, an expert in qualitative research, and an expert in mixed methods research to help with dialogue and continual integration.
- Mixed priority designs in which the principal study results derive from the integration of qualitative and quantitative data during analysis (Creamer, 2017).
Validity and veracity is stressed in scientific approaches and strategies.
One description titles this as either SAD or MAD.
- Single approach design (SAD)(also called a “monomethod design”) only one analytic interest is pursued.
- Mixed or multiple approach design (MAD) two or more analytic interests are pursued.
Method could be a way of doing, and methodology could be a discourse about method.
Multiple methodological perspectives are exciting, to some, but are they feasible?
- Many paradigms are at odds with each other.
- Cultural issues affect world views and the way one analyses. Knowledge of a new paradigm is not enough to overcome potential biases; it must be learned through practice and experience.
- People have cognitive abilities that predispose them to particular paradigms. Quantitative research requires skills of data-analysis and several techniques of statistic reasoning, while qualitative research is rooted in in-depth observation, comparative thinking, interpretative skills and interpersonal ability.
Both a qualitative and ethnographic approach requires specific expertise, ability and skills.
This is #500daysofAI and you are reading article 367. I am writing one new article about or related to artificial intelligence every day for 500 days. My focus for day 300–400 is mostly about AI, hardware and the climate crisis.