At the Association for the Study of Higher Education (ASHE) conference in November, Drs. Christen Priddie (National Survey of Student Engagement) and Rachel Renbarger (Accelerating Systemic Change Network) moderated a panel of critical quantitative scholars to discuss how higher education researchers could incorporate critical quantitative practices into their scholarship. Experts included Drs. Katherine Cho (Miami University), Cindy Ann Kilgo (Indiana University), and Kamden Strunk (Auburn University). The session was well-attended and insightful, with key takeaways for 4 main questions that were established with panelist prior to the session:
- What is critical quantitative research? What are its goals?
Critical quantitative research may not be possible to define, although the panelists did use key terms when describing it. They used terms such as systematic, systemic, and anti-positivistic and stated that critical quantitative includes an examination of race and racism within the analysis and interpretation, but also within the inclusion of theory. Ultimately, the goal of critical quantitative research would be for societal equity and ideally critical quantitative research would soon become the norm rather than the exception when it comes to education research.
- How have scholars learned how to do critical quantitative work?
All of the panelists and moderators learned how to do quantitative research from an “objective,” positivist lens, but through their doctoral work realized that research was problematic (including their own work!) because of issues with variable, coding, analysis, and model choices. Indeed, Dr. Kilgo reflected that “How can I be objective when I get to choose what goes into the model and how I interpret it?” These choices demonstrate the power that researchers have within the seemingly unaffected quantitative science. Learning how to do this work came from learning from others, including qualitative researchers and communities of color who had been challenging research norms for a long time.
- What does critical quantitative research look like from the beginning to the end of a project?
Panelists described the difficulties for quantitative researchers who are brought in after data collection which results in their objective centering on harm reduction rather than true critical quantitative work. Ideally, critical quantitative research occurs through every step of the process, from choosing a theoretical framework to writing up the findings. Dr. Cho stated that this work happens even within the literature review stages: “Does this gap in the literature actually exist? Does this research question even need to be analyzed?” This is because researchers often do not read the work of marginalized communities who have already solved these problems. Researchers should also ask themselves who this work is for; participants should want this research question answered and check to ensure they are not recreating harm through any sort of eugenics framing. When reporting, researchers should tell stories with the data, explain the results that will have actual utility for participant groups, policymakers, and practitioners, and avoid recreating harm (i.e., pitting groups against each other, perpetuating stereotypes) in what gets published. In each step of the process, researchers must think through and justify their research decisions while understanding that internalized and unchecked biases (e.g. racism, classism, sexism, heteronormativity, etc.) can harm our participants.
- How can we collaborate with other researchers who are less familiar with critical quantitative work?
As with any collaborative work, panelists suggested finding colleagues who were open to new ideas and feedback during the research process. Dr. Strunk mentioned that, like anything, there is a distribution of colleagues’ willingness to interrogate their own thinking and processes. Identifying colleagues who understand the need for critical work can help prevent research projects getting stuck or not turning out the way it was intended. Critical quantitative researchers should not act like they’re the authority, but be willing to provide stories, explanations, or readings for colleagues who do not understand epistemological or methodological approaches.
In sum, critical quantitative work does not have an easy formula or guidebook; researchers must think deeply about their own perspective and system inequities at all points of the research process. For folks interested in engaging in critical quantitative work, please see resources mentioned in the session (along with those on Dr. Cho’s website):
- Patel, L. (2015). Decolonizing educational research: From ownership to answerability. Routledge.
- Zuberi, T. (2001). Thicker than blood: How racial statistics lie. University of Minnesota Press.
- Zuberi, T., & Bonilla-Silva, E. (Eds.). (2008). White logic, white methods: Racism and methodology. Rowman & Littlefield Publishers.
- Garcia, N. M., López, N. & Vélez, V. N. (2018). QuantCrit: Rectifying quantitative methods through critical race theory. Race Ethnicity and Education, 21(2), 149-157. https://doi.org/10.1080/13613324.2017.1377675
- Gillborn, D., Warmington, P., & Demack, S. (2018). QuantCrit: Education, policy, ‘Big Data’ and principles for a critical race theory of statistics. Race Ethnicity and Education, 21(2), 158-179. https://doi.org/10.1080/13613324.2017.1377417
- Harper, S. R. (2012). Race without racism: How higher education researchers minimize racist institutional norms. The Review of Higher Education, 36(1), 9-29.
- Strunk, K., & Hoover, P. (2019). Quantitative methods for social justice and equity: Theoretical and practical considerations. In K. Strunk & L. Locke (Eds.), Research methods for social justice and equity in education (pp. 191-203). Palgrave Macmillan. https://doi.org/10.1007/978-3-030-05900-2