Title: STEM faculty who believe ability is fixed have larger racial achievement gaps and inspire less student motivation in their classes
Authors: Elizabeth A. Canning, Katherine Muenks, Dorainne J. Green, Mary C. Murphy
First Author’s Institution: Indiana University
Journal: Science Advances 5, 2019
Despite years of programs aimed at increasing the number of underrepresented people in science, technology, engineering, and mathematics (STEM) fields, Black, Latinx, and Native American students still remain substantially underrepresented and often suffer from an achievement gap, in which White and Asian students tend to perform better than students from underrepresented groups. While there are various economic and structural factors that contribute to this gap, little research has examined how faculty’s beliefs may contribute to the gap. For example, a faculty member’s views about intelligence and ability and which groups are more or less likely to have ability in STEM may have implications on how students perform in their class. The goal of today’s paper is to explore how these views may impact underrepresented students’ motivation and academic achievement in STEM courses.
To narrow down the possible faculty views, the researchers decided compare faculty with fixed mindsets to faculty with growth mindsets. Broadly, a fixed mindset is the idea that intelligence and ability are set at birth and cannot be changed. As a result, success is determined by talent rather than effort. In contrast, a growth mindset is the idea that intelligence and ability are not fixed and can be developed with effort, persistence, and quality mentoring. Prior work has shown that professors with a fixed mindset are more likely to judge students as having low ability after a single exam and are more likely to encourage students to drop difficult courses. As cultural stereotypes often portray White and Asian students as more gifted in STEM, fixed mindset professors may be especially demotivating to underrepresented students, leading to underperformance relative to their non-minority peers.
To test this idea, the researchers collected data across 7 semesters of STEM courses at a large, selective public research university, covering 15,466 students and 150 faculty in 13 STEM disciplines. Data on the students was collected through the university records and end of semester course evaluations. Data on the instructor’s mindset was collected as part of a survey which included two items on mindset that faculty were asked to rate how much they agreed or disagreed with the statements. The survey had a response rate of about 41% and roughly 10% of the students in this study identified as underrepresented.
When analyzing their data, the researchers found that on average, all students tended to perform worse in classes taught by a fixed mindset instructor and that White and Asian students tended to earn higher grades than underrepresented students. When the instructor had a growth mindset, the average difference in grades between non-underrepresented and underrepresented students corresponded to 0.10 GPA points on a 0-4.0 scale. In contrast, when the instructor had a fixed mindset, the average difference in grades corresponded to a 0.19 difference in GPA points, nearly double the size of the gap when a growth-mindset instructor taught the course (figure 1).
Next, the researchers investigated which faculty were more likely to have fixed mindsets. Interestingly, they found there were no significant differences among who was likely to have a fixed mindset based on faculty demographics. That is being of a certain gender or race/ethnicity, having tenure, how long the instructor had been teaching, and which STEM discipline they belong to did not increase the likelihood of having a fixed mindset. In addition, the researchers found that if the instructor had a fixed mindset but also identified as an underrepresented minority themselves, the gap in grades between non-underrepresented and underrepresented students did not change.
Finally, the researchers looked at student course evaluations to examine any possible differences in motivation. Indeed, the researchers found that students who had an instructor with a fixed mindset reported less “motivation to do their best work” and that their instructor was less likely to use pedagogical practices that “emphasize learning and development.” The researchers found that these less motivating pedagogical practices were associated with lower course performance. In addition, the researchers thought that perhaps fixed mindset instructors had greater demands in their course that could explain some of the results. However, students reported spending about equal amount of time on their courses, regardless of whether it was taught by a fixed mindset instructor or a growth mindset instructor (figure 2).
To explain their results, the researchers suggested that a fixed mindset may make group ability stereotypes more noticeable, resulting in stereotype threat. This can be further compounded by other recent findings suggesting that minority students who expect to be stereotyped experience less belonging, less trust, more anxiety, and become less interested. While the gap in performance may not appear to be significant, the researchers note that the gap can mean the difference between the student continuing to the next course in the major sequence or not, decreasing the number of underrepresented students earning STEM degrees.
The results of this work suggest that a growth mindset can reduce the size of the racial/ethnic achievement gap. As the researchers found that the instructor’s mindset was more important than the STEM discipline they belonged to, the culture of the discipline does not need to be changed to observe a decrease in the gap; instead, changing the mindset of individual faculty would help close the gap. Based on the results of this study, the researchers suggest that efforts to increase the number of underrepresented students earning STEM degrees should not only focus on the students and structural factors, but also should focus on instructors and how their beliefs may be contributing to an achievement gap between non-underrepresented and underrepresented students.
Figures used under Creative Commons Attribution-NonCommercial License 4.0.
I am a physics graduate student at Michigan State University and the founder of PERbites. I’m interested in applying machine learning to analyze educational datasets and how students use computation in physics courses.