Over the winter break, I’m reading José Antonio Bowen’s new book Teaching Change: How to Develop Independent Thinkers Using Relationships, Resilience, and Reflection with a couple of colleagues. While the book was just released last fall, I saw Bowen speak at a conference before the pandemic started and he previewed some of the concepts there. The book is an attempt to educate collegiate faculty on the science of learning while also informing classroom practice. While the book covers a lot of territory, its main goal is promoting teaching strategies that can foster students’ critical thinking.
Buried in a chapter titled “The Difficulty with Thinking with Others,” Bowen shared some research that made me think about a blog post I wrote last September. In the post, I wrote about my effort to take a politically neutral stance in my classroom over the years and how I worried about my students’ responses if I differed politically from them. In that post, I discussed some research I had heard on the Hidden Brain podcast that involved sports team affiliations. While the research didn’t focus specifically on political backgrounds, I drew on the work to ground my neutrality decision. In his book, however, Bowen offers a more direct connection for my neutrality stance.
Bowen presents research conducted by Guilbeault, Becker & Centola (2018) who examined the impacts of political affiliation on social learning. Using an online surveying platform, the researchers organized groups of participants with equal numbers of Republicans and Democrats in each group. The groups were shown historical data on the depth of Arctic Sea ice from 1979 – 2013 and asked to draw on the data to individually predict the current sea ice depth. While the overall trend of the data shows the depth of ice is shrinking, the data also fluctuates from year to year. The last year shown (2013) showed a marked increase in depth from the previous year. To study the impact of political affiliation, the researchers examined four separate conditions.
In one group, participants were asked to examine the data and individually predict the current sea ice depth. The participants were asked to reflect further on the data and were prompted to make two more predictions. This served as the control group since the individuals didn’t really interact with one another.
In the second group, participants were again asked to examine the data and individually predict the current sea ice depth. Average predictions were calculated then shared with the group. Participants were then prompted to predict again. After the second round, new averages were calculated and shared with the group. The participants then predicted again.
The third group didn’t differ much from the second group in terms of research process. Each participant made predictions and averages were calculated and shared with the rest group. The participants again made two more predictions based on the group averages. While the overall process didn’t change from the second group, the individuals were shown the logos from the two political parties to remind them of the diversity of the group and of their own political affiliations.
Participants in the fourth group still made predictions based on sea ice data but were shown the estimates and political affiliations of the other members of their group before they made additional predictions.
Examining the findings, the researchers found that sharing group results helped individuals make more accurate subsequent predictions. An individual’s accuracy, however, was impacted by the “political salience” present in the groups. The researchers write:
“Our findings show that when the salience of political partisanship is increased, even through minimal partisan priming, this social learning effect can be reduced, and belief polarization can be sustained. Our findings thus offer a cautionary conclusion. Politically diverse communication networks can indeed eliminate partisan bias in the interpretation of climate data but increasing the salience of partisanship can significantly limit the effectiveness of social learning.” (p. 9718).
Returning to my original post, I wrote “I worry that identifying as either a Democrat or a Republican within the classroom space would undermine my ability to be supportive and effective to all of my students.” If my goal is to support student learning, I now think it’s clear that I can be more effective coming from a position of political neutrality than trying to politicize the classroom environment.
Bowen, J. A. (2021). Teaching Change: How to Develop Independent Thinkers Using Relationships, Resilience, and Reflection. JHU Press.
Guilbeault, D., Becker, J., & Centola, D. (2018). Social learning and partisan bias in the interpretation of climate trends. Proceedings of the National Academy of Sciences, 115(39), 9714-9719.