Toward Determining Changes in Engineering-Related Social Capital: Resource Composition as Students Make Decisions About College

Matthew K. Miller, Julie P. Martin, Marisa K. Orr


Applying Lin’s Network Theory of Social Capital, a survey instrument developed by the research team was used to capture information regarding the size, structure, and composition of students’ social networks and resources related to engineering studies and careers. Data were collected from 1,410 undergraduate engineering students at five institutions in the United States. Participants were asked to reflect back to the time when they were deciding to major in engineering, identify names of people they considered influential to their decision (forming their engineering-related social network), and identify resources that were accessed through these networks. Cluster analysis was used to group participants according to social capital characteristics including network size, strength of ties, heterophily or diversity of relationships, and embedded resources. Two separate cluster analyses were conducted. The analysis based on social network characteristics yielded a three-cluster solution, identifying one group with larger networks consisting of both strong and weak ties, and two groups with smaller networks, one reporting more use of strong, family-based ties and the other reporting more influence from weaker, non-family ties. The analysis based on engineering-related resources grouped students into two categories: one reporting higher access to engineering-related resources and another group which reported, on average, lower access to each resource. Demographic analyses of the clusters revealed lower resource access was most often reported by Hispanic, first generation in college, and lower-income students while higher resource access was reported by more students who have an engineer parent or who knew an engineer before college.

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