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Inclusive Excellence in STEM

By Erika Nadile, Assistant Director of STEM Education

Active learning, a method encompassing a broad range of techniques to engage students in their own learning, decreases failing (Freeman et al., 2014) and closes "achievement gaps" (Theobald et al., 2020)—differences measured by academic performance (e.g., grades). Despite its effectiveness, the high attrition rate of students with identities and backgrounds historically underserved in higher education remains a persistent problem, even in classes that have fully transitioned to active learning. This attrition is even more pronounced in undergraduate STEM majors, where—in the words of David Asai, Senior Director for Science Education at the Howard Hughes Medical Institute—"students leave science almost as quickly as they arrive” (Asai, 2020a). Asai highlights how Persons Excluded due to Ethnicity or Race (PEERs) are overrepresented when looking at entrance into STEM disciplines but leave at greater rates compared to non-PEERs (Asai, 2020a; Asai, 2020b), even if equally motivated upon entry.  

In a peer-reviewed study conducted under the mentorship of Dr. Naomi Wernick-Pfaffmann, I demonstrate how intrinsic motivation (i.e., the drive to learn for learning’s sake) and self-efficacy (i.e., confidence), not just grades, change and differentially impact PEERs. The study findings add to the robust literature on active learning at the individual- and classroom-levels to further enhance how we think about equitable STEM education. 

Interest in this research started on a deeply personal and observational level as a first-generation, lower income (FGLI) college student and white woman in science. As an undergraduate and someone who was a biology major and then switched out to psychology, and then immediately back to biology, I remember looking around in the classroom, asking if others were like me, driving me to get involved in research on this topic. I was inspired to take what we know from the psychology literature and apply it in spaces where affective outcomes, like feelings and attitudes, are often not discussed, but are well-documented, to impact learning and extend beyond performance measures. For instance, extrinsic motivation undermines the drive to learn (Ryan and Deci, 2000)—so why keep exploring only performance goals that do not tell us the whole story?  

Studying over 100 students at a public institution in the Northeast, we demonstrate that students who are first-generation and underrepresented in science, start as equally intrinsically motivated and confident in their abilities to learn at the start of the semester in an introductory biology course. Alarmingly, both outcomes decline over only one semester. Importantly, this decline was only seen in first-generation PEERs, not continuing generation non-PEERs, a distinction which had not been well-documented in the literature, as most studies do not disaggregate among groups when exploring motivation. Our findings are present after course transition to active learning, and interestingly changes were observed with a decline in DFW rates (i.e., the number of students who receive Ds, Fs, or withdraw), while controlling for student SAT scores, suggesting active learning was “working.”   

We now have insight into when particular learners might consider leaving just by examining a single active learning course starting from a place of personal interest. I urge instructors to tap into what intrinsically motivates their students at the start of the course and implement ways to monitor changes in motivation—using pre-, mid-, and post-surveys, especially if already using active learning. Exploring performance outcomes is only the starting place to advance STEM education, and the study findings and methodology will fuel how we develop the forthcoming STEM Education Initiatives at Searle by centering multi-vocal evidence and experiences at a variety of levels—core values at Searle that we are excited to share with the Northwestern community.

 

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References

  • Asai, D. (2020). Excluded. Journal of microbiology & biology education, 21(1), 10-1128. 
  • Asai, D. J. (2020). Race matters. Cell, 181(4), 754-757. 
  • Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., & Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering, and mathematics. Proceedings of the national academy of sciences, 111(23), 8410-8415. 
  • Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary educational psychology, 25(1), 54-67. 
  • Theobald, E. J., Hill, M. J., Tran, E., Agrawal, S., Arroyo, E. N., Behling, S., ... & Freeman, S. (2020). Active learning narrows achievement gaps for underrepresented students in undergraduate science, technology, engineering, and math. Proceedings of the National Academy of Sciences, 117(12), 6476-6483.