Vague research question formulation and incohesive sampling system have led to comparatively poor saturation of the results. Low levels of saturation lead to an impossibility of replicating the research conducted and, therefore, makes it difficult to verify (Guest et al., 2020). The sampling techniques in particular appear to be a serious issue with the research conducted, since the nominally random group of university stakeholders was not randomized properly. The authors did make a point of only including the participants who were knowledgeable and experienced in their respective fields. However, the report did not involve any comments on the techniques implemented to ensure randomization, therefore making it questionable. As a result, there is a notable probability of unaccounted biases stemming from various factors of influence of the participants, such as economic background, gender or age.
Several ways of improving data saturation of the outlined research can be implemented to ensure greater study efficiency and replicability. As the term itself refers to a state where no further data collection is required, recruiting a greater number of participants would be the obvious first step. As specified above, the rigid qualification-focused requirements benefit the purpose of the research, while the imperfect randomization does not. By increasing the number of participants and refining the approach to them, the authors would be able to improve their overall sampling quality (Saunders et al., 2017). Consecutively, the data collected from the sample would become more saturated and replicable by future researchers within the field. Secondly, the research question itself could be modified towards greater precision, to ensure the time of the participants is being utilized in an efficient capacity. If the sample members clearly realize what is required of them, they are more likely to provide the interviewers with high-quality data.
References
Guest, G., Namey, E., & Chen, M. (2020). A simple method to assess and report thematic saturation in qualitative research. PLOS ONE, 15(5), e0232076. Web.
Saunders, B., Sim, J., Kingstone, T., Baker, S., Waterfield, J., & Bartlam, B. et al. (2017). Saturation in qualitative research: exploring its conceptualization and operationalization. Quality & Quantity, 52(4), 1893-1907. Web.