Author(s):
This project aims to better understand how students are using makerspaces. Using makerspaces to support engineering coursework can have mixed effects on students’ tool use. There is a general trend that students who use the space for class often find their way to other tools; however, when personal projects are not allowed, this trend is limited. This trend, however, is not consistent across tools or institutions, potentially because the tool training requirements, types of projects, and curriculum of making related courses vary substantially from course to course, as well as between institutions. By applying network analysis, which has not yet been used in the study of makerspaces prior to the work of this grant, a holistic model of makerspaces at various universities can be generated, providing insight into what features of the spaces are valuable and which are not. Bipartite networks of the two makerspaces were created from simple end-of-the-semester surveys asking students which tools they had used. The bipartite network visualizes the interactions between two groups, students and tools. Modularity, nestedness, and connectance network analyses were used to quantitatively capture patterns and trends among the makerspace networks. The COVID-19 restriction allowed for evaluation of the space when severe restrictions were placed in the space and under much more normal operating conditions a couple of years later. The method enables quantitative tracking the health of the makerspace. The two makerspaces were found to have responded very differently to the disruption, though both saw a decline in usage, the space’s overall health, and had different recoveries. Network analysis is shown to be a valuable method to evaluate the functionality of makerspaces and identify if and how much they change, potentially serving as indicators of unseen issues.
Coauthors
Pepito Thelly, and Astrid Layton, Texas A&M University, College Station, TX
