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Researchers have pointed to Wright State’s Introductory Mathematics for Engineering Applications course as a model for undergraduate engineering education curricular reform. The work behind the Wright State Model (WSM) demonstrates that adoption of its introductory course can increase engineering student retention, motivation, and academic success (N. Klingbeil, Mercer, Rattan, Raymer, & Reynolds, 2006; N. Klingbeil & Bourne, 2013), and can remove “the first-year bottleneck” associated with the traditional first-year calculus sequence (Ohland, Yuhasz, & Sill, 2004; N. Klingbeil & Bourne, 2013; Long, Abrams, Barclay, & Paulson, 2016). Klingbeil & Bourne (2013) point to the promise of the Wright State Model in engineering education reform, claiming that the model “is designed to be readily adopted by any institution employing a traditional engineering curriculum… should it be sufficiently scaled… the Wright State approach has the potential to double the number of our nation’s engineering graduates, while both maintaining their quality and increasing their diversity” (p. 10, emphasis added). In our analysis, we reconsider the “diffusion” notion of “scaling” as it is typically used in educational research (McDonald, Keesler, Kauffman, & Schneider, 2006), proposing instead that innovations and adaptations are better conceived in terms of what educational anthropologists have called “scale-making” (Nespor, 2004). According to this perspective, scale-making is an active process of forming connections between, on one hand, new practices such as the WSM course, and on the other hand, existing networks that operate at a broader spatiotemporal scale—such as classrooms, course scheduling, course numbering, curricular flowcharts, and instructional staffing and student registration practices. This paper draws on a qualitative dataset of student responses to biweekly “reflection questions” integrated into routine course activity in a pilot implementation of a Wright State-like Engineering Mathematics course. Alongside auto-ethnographic data from the course instructor and coordinator, this dataset illustrates the transformations involved in the scale-making process, and enables tracing the consequences of these transformations for the identities of people and social collectives involved in the course.
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Tsai et al. (2020) studied this question.