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Title: Makerspace Network Analysis for Identifying Student Demographic Usage
Makerspaces provide unparalleled hands-on experiences for students. Understanding the interactions that occur in these spaces is critical to improving engineering education. This work represents the first time that demographic-based modularity analysis has been conducted on university makerspaces. While largely dependent on the survey data used to make the bipartite networks, the results serve as an example of how this technique could offer a novel means of viewing these makerspaces. At the broadest level, this approach provides insight into the ways in which different subsets of students use the space, both in terms of raw usage statistics and in terms of the module assignments for both student and tool groupings. When looking at the network from a major perspective, the desired change in modularity is less apparent, and more work will need to be done to see whether increasing the modularity helps with system resilience (maintaining high levels of makerspace operation despite failures of certain tools) or if higher modularity represents an undesirable separation in the space between different majors and the tools they tend to use.  more » « less
Award ID(s):
2013547
PAR ID:
10412258
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
2022 International Symposium on Academic Makerspaces (ISAM)
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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