2025 ASEE Annual Conference & Exposition

Makerspaces are becoming a staple at engineering institutions of all sizes worldwide. These spaces allow for conceptual design problems and solutions to be practically realized by making the tools and resources needed accessible to students. Due to their widespread adoption, it is prudent to understand the characteristics of effective and ineffective student and tool usage patterns. Makerspace researchers have adopted network analysis techniques commonly used by ecologists to quantify mutualistic ecosystem usage patterns, for example interactions between plants and pollinators, to both understand and analyze student-tool interactions. In line with prior studies where makerspaces were visualized as bipartite networks (student users and tools are treated as two distinct actor groups and the interactions between them captured visually in a network graph and quantitatively in an interaction matrix), the work here further projects this user-tool bipartite network onto itself to arrive at a tool-tool makerspace network model. The goal for this approach is to highlight the interactions between tools as determined by common users. Makerspaces at two large universities in the United States are used as case studies for this analysis, with one space only allowing course projects (School A) and the other allowing both course and personal projects (School B). Prior work calculated a participation coefficient and within-module degree for both schools, network graph metrics that were found to reveal how adeptly actors interact with others inside and outside of their tool clusters or modules. This work concluded that School B, characterized by its allowance of personal projects, saw a higher level of interactions between modules. Building on that work here, tool-tool network densities provide deeper insights into tool usage patterns both during and recovering from COVID-19 restrictions. In the context of the tool-tool networks, a higher network density indicates that more tools are being used by the same users, possibly implying a greater potential for collaboration between users. The analysis finds that density values are consistently higher at School B both during and after the disturbance. A potential tool usage trend emerges, possibly due to personal projects being allowed and encouraged at School B, where common tool usage may imply more users are collaborating (another important skill for engineering students entering the workforce). Additional work is required to clarify these conclusions regarding the relationship that project types may have on intra-network connectivity and collaboration in engineering makerspaces. This project was funded by the National Science Foundation’s Improving Undergraduate STEM Education (IUSE) program.