Hi
I am teaching a Course in Data Science, and I am looking for a reference on general research design / design of study which can be used is this context.
I am looking for something which is not a full book, but rather of article length that potentially covers a classical approach to research design (i.e. what do you need to consider when doing research) and a view on the same in a data science perspective.
It can of course be a number of articles covering different aspects.
I hope someone has a good idea :-)
/Martin
A Chapter of Book named "Marketing Research" by N Malhotra is best in my opinion. It covers all kind of research design in simplified way.
The guidance / illustrations as per the following publications may further help:
- Asenahabi, B. M. (2019) Basics of research design: A guide to selecting appropriate research design, International Journal of Contemporary Applied Researches, 6, 5, pp. 76-89.
- Choy, L. T. (2014) The strengths and weaknesses of research methodology: Comparison and complimentary between qualitative and quantitative approaches, IOSR Journal of Humanities and Social Science, 19, 4, pp. 99-104.
- Creswell, J. W., Hanson, W. E., Plano-Clark, V. L. and Morales, A. (2007) Qualitative Research Designs: Selection and Implementation, The Counseling Psychologist, 35, 2, pp. 236-264.
- de Vaus, D. (2001) What is Research Design / Tools for Research Design, in de Vaus, D. (ed.) Research Design in Social Research. London: SAGE Publications Ltd, pp. 1-32.
- Edelson, D. C. (2002) Design research: What we learn when we engage in design, The Journal of the Learning sciences, 11, 1, pp. 105-121.
- Tomaszewski, L. E., Zarestky, J. and Gonzalez, E. (2020) Planning qualitative research: design and decision making for new researchers, International Journal of Qualitative Methods, 19, pp. 1-7.
Hi Martin,
I thought about this a bit and I think I cannot answer well without more context. General research design is way too broad. To move forward, I would find it helpful to formulate a more specific aim for the Data Science context. I can offer a few possibilities:
Is the goal to communicate a research design that can distinguish descriptive, associative and causal findings?
Is the goal to communicate that role of different methods (qual/quant)?
Do we want to be specific about the role of theory and generalisations? In more practical terms, this could probably be translated to language of inductive and deductive reasoning processes.
This is a really cool problem to think about. I would be intrigued to talk more about the boundary between approach to research as science (some version of the scientific method) and the data science process. They are kind of both similar and different in ways that would be worth looking into.
Btw, I took your class in 2016? :D
Hi Martin,
Russell Poldrack, psychologist from Stanford University, wrote/is writing an open book on statistical thinking. Although his focus is on statistics, he also covers topics typically tought in experimental research such as validity and reliabilty. Maybe you find some useful content there. You may have a look at https://statsthinking21.github.io/statsthinking21-core-site/index.html
Cheers
Nick
- Badges
- Science method
- Similar topics
- Teaching