2017 ASEE Annual Conference & Exposition

The purpose of this research paper is to understand how diverse students are incorporated into the social structures of a first-year engineering course. Engineering is becoming an increasingly interconnected field, creating the necessity for engineers to be capable of working with diverse personnel. The collaborative nature of engineering stipulates that engineering programs develop technically and socially proficient engineers. Research has shown that working with diverse individuals increases the quality of solutions when compared to working on homogeneous teams. One mechanism for improving students’ ability to work with diverse individuals is through meaningful social interactions. Social interactions have been shown to improve student outcomes including persistence, engagement, increased design performance, creativity, and increased student expectations of diversity among peers. Social network analysis (SNA) provides a set of tools that allow the structure of social interactions to be analyzed, including measures of network inclusiveness. This work seeks to build on previous research examining student social interactions in science, technology, engineering, and mathematics (STEM) education, that shows social interactions create learning gains. Using SNA in a large first-semester engineering course, this work examines if social interactions can foster the inclusion of diverse into the social structures of the course.

A social networking instrument previously used by other researchers in an introductory physics class was adapted for a pilot study in a first-year engineering course (n = 861). This instrument captured interactions within assigned teams but failed to represent how students interacted within the larger peer group outside of assigned teams. To address our research question, a greater level of detail was needed. Therefore, the instrument underwent several iterations, during each iteration evidence for content validity was gathered using a network of experienced engineering education and social network researchers. The second iteration of the SNA survey was then administered to a second pilot group (n = 48) of engineering students in a summer physics course. This administration of the instrument showed that the revised instrument could capture student interactions beyond assigned teams. The final iteration focused on ensuring the instrument was easily deployed and scalable for use in a large first-year engineering course.

The final social networking survey was administered in a first-year engineering course at a western land-grant institution (n = 498, 71% response rate). Initial results indicate that the instrument is capturing student interactions beyond assigned teams. This increased level of detail allows for a more representative picture of the students’ social network. Using the measures of network centrality and density, inclusiveness (or the lack thereof) of diverse individuals can be characterized. These measures allow for an empirical understanding of the explicit connection between social interactions and inclusiveness in first-year engineering courses. Understanding these connections can allow us to begin to address factors that may contribute to warming the chilly climate of engineering.