Abstract
Abstract
Background
The ability to navigate obstacles and embrace iteration following failure is a hallmark of a scientific disposition and is hypothesized to increase students’ persistence in science, technology, engineering, and mathematics (STEM). However, this ability is often not explicitly explored or addressed by STEM instructors. Recent collective interest brought together STEM instructors, psychologists, and education researchers through the National Science Foundation (NSF) research collaborative Factors affecting Learning, Attitudes, and Mindsets in Education network (FLAMEnet) to investigate intrapersonal elements (e.g., individual differences, affect, motivation) that may influence students’ STEM persistence. One such element is fear of failure (FF), a complex interplay of emotion and cognition occurring when a student believes they may not be able to meet the needs of an achievement context. A validated measure for assessing FF, the Performance Failure Appraisal Inventory (PFAI) exists in the psychological literature. However, this measure was validated in community, athletic, and general undergraduate samples, which may not accurately reflect the motivations, experiences, and diversity of undergraduate STEM students. Given the potential role of FF in STEM student persistence and motivation, we felt it important to determine if this measure accurately assessed FF for STEM undergraduates, and if not, how we could improve upon or adapt it for this purpose.
Results
Using exploratory and confirmatory factor analysis and cognitive interviews, we re-validated the PFAI with a sample of undergraduates enrolled in STEM courses, primarily introductory biology and chemistry. Results indicate that a modified 15-item four-factor structure is more appropriate for assessing levels of FF in STEM students, particularly among those from groups underrepresented in STEM.
Conclusions
In addition to presenting an alternate factor structure, our data suggest that using the original form of the PFAI measure may significantly misrepresent levels of FF in the STEM context. This paper details our collaborative validation process and discusses implications of the results for choosing, using, and interpreting psychological assessment tools within STEM undergraduate populations.
Publisher
Springer Science and Business Media LLC
Reference128 articles.
1. Akaike, H. (1998). Information theory and an extension of the maximum likelihood principle. In Selected papers of Hirotugu Akaike (pp. 199-213). New York, NY: Springer.
2. Aronson, J., Fried, C. B., & Good, C. (2002). Reducing the effects of stereotype threat on African American college students by shaping theories of intelligence. Journal of Experimental Social Psychology, 38(2), 113–125. https://doi.org/10.1006/jesp.2001.1491.
3. Asai, D. J. (2020). Race matters. Cell, 181(4), 754–757. https://doi.org/10.1016/j.cell.2020.03.044.
4. Asparouhov, T., & Muthén, B. (2018). SRMR in Mplus. Retrieved from Mplus Web Notes website:http://www.statmodel.com/download/SRMR2.pdf.
5. Auchincloss, L., Laursen, S. L., Branchaw, J. L., Eagan, K., Graham, M., Hanauer, D. I., … Dolan, E. L. (2014). Assessment of course-based undergraduate research experiences: A meeting report. CBE-Life Sciences Education, 13(1), 29–40. https://doi.org/10.1187/cbe.14-01-0004.
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