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Qualitative Research Designs
Qualitative research delves into experiences and attitudes of research subjects by answering questions about the “what”, “how” or “why” of a phenomenon.
Strengths
It is based on subjective experiences of the researcher and his research subjects. Since the researchers do not know in advance what they are looking for, it is done at the initial stages of a research to get a comprehensive understanding of the potential causes of a problem(Curry, Nembhard, & Bradley, 2009)
Weaknesses
Since it focuses on the subjective opinions and experiences, the number of research participants is usually low, because of limited resources available to study research subjects in depth. As a hypothesis cannot be formulated before the conduct of such research, an inductive method is used to extrapolate data from a small sample to a large population where there cannot be a testing of hypothesis. More time might be required to complete qualitative studies. The very subjective nature of qualitative research can introduce a researcher bias into the data. The same study repeated a second time might not produce the same findings because of the subjective variability of data.
Quantitative Research Designs: Quantitative research measures data in the form of numbers. It answers questions like “ how many” and “ how much”.
Strengths: This research is based on objective numeric data, collected during the testing of a hypothesis. Since the involvement with the research participants is limited, the researcher analyses data with minimal involvement with either the subject or his data. Since hypotheses are formulated before the conduct of the research, such studies allow for “hypothesis testing”. Compared to qualitative research, less resource allocation is required for the numbers of participants involved. Such studies are repeatable using the same quantified methodologies and formulae(McCusker & Gunaydin, 2014; Yilmaz, 2013)
Weaknesses: The researcher chooses and restricts information required, through formal data collection tools. Since data is collected from larger samples of participants, attention is paid to statistical testing of numbers rather than individual opinions and viewpoints. The quality of the raw data is important in quantitative research unlike qualitative, where the researcher, who analyses data ensures data quality through its interpretation (Harwell, 2011).
References
Curry, L. A., Nembhard, I. M., & Bradley, E. H. (2009). Qualitative and mixed methods provide unique contributions to outcomes research. Circulation, 119(10), 1442–52. doi:10.1161/CIRCULATIONAHA.107.742775
Harwell, M. R. (2011). Research Design in Qualitative/Quantitative/ Mixed Methods. Opportunities and Challenges in Designing and Conducting Inquiry, University of Minesotta, 147–182. doi:10.4135/9781412961288.n380
McCusker, K., & Gunaydin, S. (2014). Research using qualitative, quantitative or mixed methods and choice based on the research. Perfusion, 0267659114559116. doi:10.1177/0267659114559116
Yilmaz, K. (2013). Comparison of quantitative and qualitative research traditions: Epistemological, theoretical, and methodological differences. European Journal of Education, 48, 311–325. doi:10.1111/ejed.12014
