Campus Connections: Student and Course Networks in Higher Education

Abstract

Residential higher education brings thousands of students together for multiple years and offers them an array of shared intellectual experiences and a network of social interactions. Many of these intellectual and social connections are formed during courses. Students are connected to students through courses they take together, and courses are connected to one another by students who take both. These courses and the students who take them form a bipartite network that encodes information about campus structures and student experiences. Because all institutions of higher education collect and maintain precise records of what courses students take, it is possible to assemble a student-course network that quantitatively describes the interactions among students and courses. We provide an example that demonstrates the identification of courses effective at creating unique connections among students and reveals how students and majors can be strongly connected or dispersed. We show how social network analysis can be used to improve our understanding of the learning environment at the University

The Small-World Network of College Classes: Implications for Epidemic Spread on a University Campus

“…Our hope is that this will provide a starting point for network epidemiologists who do wish to estimate a predictive model under different assumptions about R0 and other parameters. Second, we advance existing empirical knowledge of the social structure of higher education, using one university as a case study (see also Israel et al 2020). Third, and perhaps most critically, we provide relevant evidence to university leaders who must balance the benefits of face-to-face instruction against the potential risk it entails, and to the faculty, staff, parents, and students who are trying to understand these decisions.…”

Mapping the landscape of a wide interdisciplinary curriculum: a network analysis of a Korean university and the lessons learnt

“…Network analysis has been used to interpret complex systems from multiple perspectives, ranging from social systems to shared knowledge networks (e.g., Aldrich 2015; Ouyang & Scharber 2017; Willcox & Huang 2017; Israel, Koester & McKay 2020; Huang & Willcox 2021). Applications of network analysis, which reveal the hidden features and relationships in higher education systems, have also been developed (Willcox & Huang 2017; Huang & Willcox 2021).…”

“…Willcox & Huang (2017) introduced an interactive curriculum map on the MIT university website () to help students create a solid curriculum path and browse similar or alternative classes. More recently, Israel et al (2020) investigated student and course networks in higher education to reveal campus connections.…”

Analysis of COVID-19 Mitigation Measures on a Small Liberal Arts College Network

“…They also simulated the network with class size thresholds that would require a course to be taught virtually. A similar study was done in [13], on the 2019 Leaming Analytics Data Architecture data set out of the University of Michigan, with a focus on how important certain courses are in creating connectivity between students.…”

“…We extend the work in [13] and [21] by considering our small, stand-alone liberal arts college and include faculty data, athletics, ensembles, housing, and student organizations to create a person-to-group network and related person-to-person network. We also simulate virtual and hybrid courses, and the result of splitting the semester into two 7-week sessions, the latter of which has a significant impact on the network analysis results.…”