As the popularity of makerspaces and maker culture has skyrocketed over the past two decades, numerous studies have been conducted to investigate the benefits of makerspaces for university students and how to best establish an inclusive, welcoming environment in these spaces on college campuses. However, unprecedented disruptions, such as the COVID-19 pandemic, have the potential to greatly affect the way that students interact with makerspaces and the benefits that result. In this study, a survey asking about prior makerspace involvement, tool usage, and student demographics was administered to students who use academic makerspaces at two large public universities. Survey data was collected for three semesters (Fall 2020, Spring 2021, and Spring 2022) and spanned both during and after the height of the COVID-19 pandemic. To quantify the differences between the semesters, nestedness and connectance metrics inspired by ecological plant-pollinator networks were utilized. These ecological metrics allow for the structure of the interactions of a network to be measured, with nestedness highlighting how students interact with tools and connectance with the quantity of student-to-tool interaction. The network analysis was used to better gauge the health of the makerspace and the type and frequency of interactions between tools. The raw survey data combined with the ecological metrics provided unique insight into the struggles the makerspaces encountered throughout the pandemic. It was found that nestedness, a measure of system stability, decreases with a decrease in tool usage. Additionally, the higher the connectance the more students interacted with the space. Utilizing metrics such as these and better understanding student tool interactions can aid makerspaces in monitoring their success and maintaining a healthy and welcoming space, as well as tracking the current health of the space. In combination with the survey results, a deep understanding of what challenges the space is facing can be captured.
This content will become publicly available on October 18, 2024
Tool Usage Patterns of Mechanical Engineering Students in Academic Makerspaces
Academic makerspaces have continued to rise in popularity as research shows the diverse benefits they provide to students. More and more engineering curriculums are incorporating makerspaces and as such there is a need to better understand how their student users can best be served. Surveys administered to makerspace users at a public research university in the Southwest United States during Fall 2020, Spring 2021, Spring 2022, and Fall 2022 tracked student tool usage trends with academic career stages. The survey asked questions about prior experience, motivation, tool usage, and demographics. Analyzed results for mechanical engineering student users provide insight into how curriculum and class year affect the specific tools used and the percentage of students who used a particular tool. The survey results also create a bipartite network model of students and tools, mimicking plant-pollinator type mutualistic networks in ecology. The bipartite network models the student interactions with the tools and visualizes how students interact with the tools. This network modeling enables ecological network analysis techniques to identify key makerspace actors quantitatively. Ecological modularity, for example, identifies divisions in the student-tool makerspace network that highlight how students from different majors (here we investigate mechanical) utilize the makerspace's tools. Modularity is also able to identify “hub” tools in the space, defined as tools central to a student's interaction within the space, based on student-tool connectivity data. The analysis finds that tools commonly used for class by mechanical engineering students, such as the 3D printer or laser cutter, act as gateway tools that bring users into the space and help spark interest in the space's other tools. Using the combined insights from the survey results and the network analysis, ecological network metrics are shown here to be a promising route for informing makerspace policy, tool purchases, and curriculum development. The results can help ensure that the space is set up to give students the best learning opportunities.
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- Award ID(s):
- 2013547
- NSF-PAR ID:
- 10498875
- Publisher / Repository:
- 2023 IEEE Frontiers in Education Conference (FIE)
- Date Published:
- Page Range / eLocation ID:
- 1-6
- Subject(s) / Keyword(s):
- ["makerspace","design","interaction networks","bioinspired design"]
- Format(s):
- Medium: X
- Location:
- College Station, TX, USA
- Sponsoring Org:
- National Science Foundation
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Abstract -
When college campuses resumed in-person learning opportunities following initial lockdowns during the COVID-19 pandemic, many facets of campus life looked different. These differences continue to evolve from semester to semester because of changing health guidelines, school decisions, and personal convictions. Academic makerspaces were not exempt from these changes and have experienced fluctuating usage and usage barriers over the past several semesters. Better understanding the effects of COVID-19 on academic makerspaces can help ensure that students continue to draw maximum benefits from these learning spaces and also provides potential advice for administrators and educators for future disturbances. Data collected via tool usage surveys administered to makerspace users at a large public university during the three semesters following the start of the pandemic (Fall 2020, Spring 2021, and Spring 2022) is used here to investigate. COVID-19 restrictions present during Fall 2020 and Spring 2021 were mostly loosened in Spring 2022. The makerspace is modeled as a bipartite network, with student and tool interactions determined via end-of-semester surveys. The network is analyzed using nestedness, a metric primarily used in ecology to evaluate the stability of an ecosystem and proposed here as a quantitative method to evaluate makerspace health. The surveys used to create the network models also provide validation, as students were asked to share tools used during the semester in question. The results suggest that nestedness is linearly proportional to usage, both increases and decreases. As such, tracking the nestedness of a makespace over time can serve as a warning that unintended restrictions are in place, intentional restrictions and/or policies may be too severe, or whether a space has effectively recovered from temporary restrictions.more » « less
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Clifford Whitcomb (Ed.)Analyzing interactions between actors from a systems perspective yields valuable information about the overall system's form and function. When this is coupled with ecological modeling and analysis techniques, biological inspiration can also be applied to these systems. The diagnostic value of three metrics frequently used to study mutualistic biological ecosystems (nestedness, modularity, and connectance) is shown here using academic engineering makerspaces. Engineering students get hands‐on usage experience with tools for personal, class, and competition‐based projects in these spaces. COVID‐19 provides a unique study of university makerspaces, enabling the analysis of makerspace health through the known disturbance and resultant regulatory changes (implementation and return to normal operations). Nestedness, modularity, and connectance are shown to provide information on space functioning in a way that enables them to serve as heuristic diagnostics tools for system conditions. The makerspaces at two large R1 universities are analyzed across multiple semesters by modeling them as bipartite student‐tool interaction networks. The results visualize the predictive ability of these metrics, finding that the makerspaces tended to be structurally nested in any one semester, however when compared to a “normal” semester the restrictions are reflected via a higher modularity. The makerspace network case studies provide insight into the use and value of quantitative ecosystem structure and function indicators for monitoring similar human‐engineered interaction networks that are normally only tracked qualitatively.more » « less
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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
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