The philosophical foundation of mixed-methods design is pragmatism, the movement that emphasizes the benefits of applying pluralistic approaches and rejects the possibility of acquiring precise knowledge about reality. Mixed-methods studies draw upon two or more theoretical perspectives or frameworks to provide a better understanding of the issue. In most cases, mixed-methods designs operate quantitative data for the assessment of the magnitude or frequency of certain phenomena, while also applying qualitative methods (e.g., interviews, case studies) to analyze the significance of these phenomena.
Therefore, mixed methods researchers can benefit from the strengths of both quantitative and qualitative approaches, thus giving more credence to their results. However, it should be noted that very few mixed-methods studies integrate qualitative and quantitative approaches to the same extent: more often, there is a well-articulated dominance of either one (Johnson, Onwuegbuzie, & Turner, 2007). Another benefit of mixed-methods design lies in the fact that it allows researchers to overcome the reductionist commitment to a single theoretical perspective, which may be alien for other researchers in this field.
Despite obvious strengths, mixed-methods design has many limitations. Primarily, a mixed-methods researcher must have outstanding competence in both qualitative and quantitative approaches, which is quite uncommon. Secondly, this design is costly and time-consuming due to the need to analyze different types of data. Thirdly, there may be significant difficulties in reconciling conflicting data and assessing qualitative data with quantitative methods. Moreover, mixed-methods design still lacks methodological and typological clarity, which is the reason for criticism and rejection on the part of “purist” researchers (Johnson, Onwuegbuzie, & Turner, 2007). Therefore, while mixed-methods design is an innovative approach that provides a holistic picture of research issues, it requires much more scrutiny, rigor and expenditures than single-method designs.