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Pedagogical innovation efforts in engineering education and other STEM fields highlight some of the inherent challenges and opportunities in the process of strengthening undergraduate education. While interactive pedagogical approaches involving peer teamwork and a mix of in-person and online resources have strengthened the quality of teaching/learning, few studies provide a close-up examination of how faculty members navigate the implementation of new learning systems developed in other institutional settings. In this paper we examine factors contributing to the lack of sustained adoption of an engineering learning system called Freeform in a new academic context. We found that while students lauded the learning system’s potential for deep learning practices, the lead instructor encountered several challenges in its implementation which precluded him from adopting the system in the long term. While the lead instructor recognized the pedagogical value of Freeform in helping students engage deeply with engineering concepts, he found its implementation to differ too greatly from his traditional teaching trajectory in addition to increasing his preparation workload and having other logistical barriers. Ultimately, Freeform was not compatible with the specific institutional culture of the engineering department where the study took place. We offer some potential solutions to ameliorate issues of compatibility when attempting to diffuse and implement pedagogical systems in different institutional contexts. 

Context: Effective reform of engineering education necessitates the widespread implementation and dissemination of pedagogical innovations globally. However, to ensure the successful propagation of these innovations, we need to better understand the adaptations that they undergo when adopted at a new institution, and the extent to which they differ from the original innovation. This includes understanding the student experience with the innovation. Purpose or Goal: This study examines the propagation and adaptation of Freeform, a learning environment for teaching an undergraduate dynamics course developed at a large Midwestern university in the United States. Specifically, our goal is to understand how students at an adopting institution used Freeform’s learning resources. Our research questions are: 1) What are the students’ archetypical patterns of resource usage at the adopting institution? 2) In what ways do those patterns differ from those of students at the original institution of Freeform? Methods We conducted a model-based clustering analysis to answer our two research questions. The analysis was conducted on survey data from 50 engineering students at the Freeform adopting institution. This data articulated how frequently students used nine different resources of the Freeform ecosystem. Outcomes: Our analysis identified 4 resource-usage patterns in the Freeform adopting institution in comparison to 9 patterns for students at the institution where Freeform originated. In the Freeform adopting institution, the most frequent resources that students utilized were Teaching Assistants (TAs) and other students who were not enrolled in the course. This contrasts with the original institution where students relied mostly on the course lecturebook and their classmates. Conclusion: This study highlights the importance of taking into consideration the differences across institutions when propagating pedagogical innovations such as Freeform. Our results suggest that instructors should anticipate those differences so that the adoption and onboarding process can be optimized for success.