2026 ASEE Annual Conference & Exposition

This work in progress submission outlines advancements in detecting interdisciplinary collaboration in undergraduate STEM student curriculum choices. Students often have a level of agency in the courses they take on their paths to graduation, opting to take courses that may not be housed in their declared major's department. This indicates that the student has knowledge, skills, or attitudes (KSAs) from several disciplines and are interdisciplinary in their education. Courses frequently chosen by students in a given domain indicate a trend that we interpret as overlap between programs. This work highlights engineering and computing programs within the larger STEM context for their histories of interdisciplinarity as well as emerging sub-disciplines (e.g. bioinformatics).

We use the MIDFIELD dataset, which provides a rich record of over 98,000 student course records from eighteen universities in the USA. These paths to graduation are analyzed to determine overlap between courses taken in and out of the students declared major. We have extended this analysis to account for not only presence of course overlap, but also magnitude, enriching the analysis and revealing a higher granularity of interpretation. Data visualization techniques are being developed to present this information in an intuitive manner.

This study aims to inform curriculum design and promote interdisciplinary collaboration both at the student level and the curriculum design level. We use student enrollment in courses as a proxy to determine what fields they invest their efforts into and possibly see as relevant for their immediate career paths or to explore alternative domains before their graduation. This also informs academic advisors about which classes have been and are likely to interest students seeking to explore courses. At the curriculum level, institutions can use this data to facilitate collaboration between known collaborator departments and to identify emerging interdisciplinary fields. Should an institution have a pairing of domains well established at their institution, a high course overlap indicates interest in collaborative curriculum development.