Mixed Methods Research

I created this paper for my graduate research methods class at the University of Rochester. The professor asked us to read, Chapter 10, Mixed Methods Research, from "Research and Evaluation in Education and Psychology," by Mertens (2019) and provide a critical analysis. I have included my analysis below.

Mixed Methods Research

This week, I chose to comment on Mertens' Chapter 10, Mixed Methods Research. Mertens' opening sentence of the chapter tells us that the use of mixed methods approaches is increasing. She offers us some straightforward definitions of mixed methods research, including the basic premise that it contains both quantitative and qualitative. Mertens gives us more details, examples, and notes that researchers must have math and word skills to conduct mixed methods.

Mertens explains how mixed methods are important in the fields of education and psychology because both these fields are so complex, and multiple perspectives are required for a complete understanding. She also mentions that every philosophical school can use mixed methods: pragmatic, constructivist, postpositivist, and transformational. Mertens talks about mixed methods design, for example, with qualitative and quantitative parts done in parallel or sequentially. Again, Mertens touches on the complexity of mixed methods and how it becomes even more important to conduct it right and carefully.

After reading this chapter, I was curious because mixed methods seem like a path for the future. From my beginning learnings, it seems there is kind of an ideological debate going on between the postpositivists and the transformationalists, with the pragmatists and constructivists left in the middle. It seems to me that mixed methods could be used to synthesize these two ideological schools.

It seems to me that mixed methods were not used in the past because it was complicated to collect and analyze big data sets, especially qualitative ones. These days, with big data and AI, we absolutely can collect, organize and investigate big data sets of both qual and quant data.

I was left wanting more after the chapter; I felt like Mertens gave us a limited overview of the topic compared to her chapter on qualitative research, which was about 48 pages in length; this mixed method was only 18. I wondered if Mertens was biased because I sensed that she over-emphasized qualitative research and was overly critical of quantitative research.

What I didn't realize until I visited Merten's website was that her career seems to have been devoted to mixed methods as a technique and the transformative paradigm, which it looks like she may have even invented. I also didn't realize until visiting her website that Mertens is deaf, so I imagine that may have profoundly shaped her experience in the world.