“Mixed Methods Research” Basic Designs and Methods: a Visualization for Teaching Purposes

Classifying mixed methods (MM) research designs is notoriously difficult and a simple visualization of MM designs for teaching purposes is lacking. To fill this gap, in this paper I introduce a visualization of basic MM research designs and methods for teaching and didactic purposes. I provide examples of how MM studies from the field of management can easily be mapped on this visualization. The visualization (Figure 1) represents three basic MM designs – exploratory sequential, explanatory sequential, and convergent, and three basic MM methods – building, connecting, and merging. The visualization utilizes a structure of a matrix, with the research steps being represented with numbers, in a process-like sequence. The numbers denote the sequence of research steps. The thickness of the arrows may be varied to denote the relative size of the qualitative or quantitative sample in a study. Figure 2 provides an example of how a MM study (Raffaelli & Glynn 2014) is mapped on my framework – the arrow in the quantitative part of the visualization is thicker, which denotes that the relative size of the quantitative sample in this study is bigger (compared to the qualitative sample). The matrix structure of the proposed visualization enables easy switching through the quadrants, without the need to draw duplicates of boxes or circles. This decreases the cognitive load necessary for comprehension, as my pilot test with PhD students has shown. Existing visualizations of MM designs and methods, like Onwuegbuzie, Slate, Leech, and Collins’s (2007) or Leech and Onwuegbuzie’s (2009), contain a multitude of boxes or circles and provide a level of detail, which may be relatively hard to comprehend by MM novices. While I fully recognize the merit and value of these visualizations for advanced MM purposes, and while I partially derive the contents of my visualization based on them (and also based on Fetters, Curry, and Creswell’s 2013 framework), I believe that they are not optimal for teaching MM to beginners. The simplified visualization, which I propose for teaching purposes, offers a clear matrix structure. Through this structure, the main steps of the MM designs are easy to follow and comprehend. I employ the power of the visual language to foster clarity. My visualization also provides an easy way to map any mixed methods study, as I show with my example MM studies. The proposed visualization is not without limitations, the biggest of which being the danger of reification because of its simplicity. While this is a valid limitation to be considered, it is moderated by the fact that this visualization is meant to be used for teaching, where simplicity is crucial. The visualization can be used by scholars for didactic purposes. It can also serve as a heuristic device to define and explicate the type of MM design utilized by various studies. Such a heuristic device is necessary for researchers seeking orientation in the MM field or seeking assistance in deciding which MM design to apply in their work. References