Challenges of Mixed-Methods and/or Cross-Disciplinary Research in Practice: An Example

• In Event: Successful Mixed-Methods and/or Multidisciplinary Team Approaches to the Study of Racial Justice/Injustice in Education

Abstract

This paper is a response to the report, “Mixed Methods for Studies That Address Broad and Enduring Issues in Education Research,” that appeared in Teachers College Record (Authors, 2019). The report’s purpose was to suggest how mixed methods research—broadly construed—might be productively used to address “broad and enduring educational problems in an increasingly unjust and unequal society.” Although the report is a useful guide to thinking about and planning for mixed methods and, by extension, cross-disciplinary research, it did not address the messy complications of actually doing mixed methods research. This paper discusses complications we faced in a recent mixed methods study of STEM education reform for underserved students.
Our research team consisted of an anthropologist, a sociologist, and a somewhat transient group of postdoctoral scholars and PhD students in educational research. Our project focused on three questions: Beginning in 2010, what steps did 8 non-privileged high schools in 2 cities take to improve STEM education? What interfered with or complicated these efforts? Did a comparable group of diverse, low-income students of color from these schools—students who were all high-achievers in math/science in grade 10 and interested in STEM--pursue STEM through high school, into college, and into work? How and why?
These questions clearly called for multiple data sources: archival and documentary evidence about the cities, school districts schools, and students; interviews with school officials, teachers, students, and community members; observations of classrooms, students, and teachers; surveys of students; and student records. We had to spend time building and maintaining relationships with schools, students, parents, and communities. We had to follow students through high school and into college or work.
Working with numerous people with different backgrounds, a lot of data, and fluctuations in circumstances over ten years led us to struggle over interpretations and integration of findings. Three sources of struggle were: integration of sociological (structure) and anthropological (meaning) orientations; conceptualizations of more versus less successful students and schools; and results from qualitative and descriptive quantitative data.
For example, we were interested in what STEM reforms were proposed and implemented in each school and how they functioned over time. But we also wanted to know what meanings students, teachers, and administrators constructed around these efforts. The two perspectives took us in different directions: toward analyses of curriculum changes on one hand and analyses of “being good” in math/science on the other. The challenge was to figure out how results from these two perspectives were interrelated. This is a common problem with cross-disciplinary research, as theoretical priorities differ by field. Further, student success as measured by number and type of STEM courses and grades did not track well with actual college and workplace outcomes; this, too, had to be reconciled.
Mixed methods/cross disciplinary perspectives and teams are enticing; they offer varying perspectives and modalities of data collection that can be brought to bear on proposals and interpretation of findings. However, investigators must continually work at communication across field and method to maximize possibilities.

Author

• Margaret A. Eisenhart, University of Colorado - Boulder