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Makerspaces have the potential to revolutionize engineering education by providing a platform for students to nurture their tacit knowledge. This unique space allows for students to work with advanced prototyping equipment, develop specialized skills and create community. Although makerspaces could become an important dimension of engineering education, it is unclear whether these spaces are inclusive for all engineering students, especially those from underrepresented groups. Specifically, this study aims to understand the experiences of diverse female engineering students in makerspaces. For this study, we analyzed interview transcripts of ten women from multiple U.S. universities housing engineering academic makerspaces—those anchored to and supported by the engineering department/school specifically—and found common themes across their stories. These themes include the perception of gender bias, as well as an intimidating, hostile, and non-inclusive environment. Although the results of this study demonstrate gender bias and marginalization occur in makerspaces, female engineering students still find value in the makerspace through access to resources, opportunities to learn, increased confidence, and female makerspace staff.
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Bipartite Network Analysis Utilizing Survey Data to Determine Student and Tool Interactions in a Makerspace
There has been dramatic growth in the number of makerspaces at educational institutions. More research is needed to understand student interactions in these spaces and how these spaces should be designed to support student learning. This project uses network analysis techniques to study the network of activities in a makerspace that lead to successful student experiences. The proposed analyses will model a makerspace as a network of interactions between equipment, staff, and students. Results from this study will help educators to 1) identify and remove previously unknown hurdles for students who rarely use the space, 2) design an effective space using limited resources, 3) understand the impact of new equipment or staff, and 4) create learning opportunities such as workshops and curriculum integration that increase student learning. The new knowledge produced by this project may be useful for maximizing equipment and support infrastructure, and for guiding new equipment purchases. Thus, the results will support further development of effective makerspaces. This project hypothesizes that network-level analyses and metrics can provide valuable insights into student learning in makerspaces and will support what-if scenarios for proposed changes in spaces. Systems modeling and analysis have been used successfully to understand complex human and biological networks. In the context of makerspaces, this technique will provide measures of interaction between system components such as students, staff, and equipment. The analyses will identify the system components that are frequently used when students work in the makerspace over multiple visits. The project will allow for the comparison of makerspaces that have different levels of integration with the curriculum and methods of student introduction (pop-up classes, tours, extra-curricular competitions, advertising, and bring a friend). Demonstration of the effectiveness of the analyses in characterizing makerspaces and the ease of data collection will help support the use of this approach in future work that compares makerspaces nationwide. Current results explore the order in which students choose to learn and use the tools in the space, which tools/features are used most frequently and how the data from the daily entry/exit surveys compares to the end-of-semester self-reports. A key question in this research, especially for making it adoptable by other universities, is if end-of-semester, self-reported data is accurate enough to create informative, actionable guidance from the network models without requiring the daily tool usage data.
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- PAR ID:
- 10331810
- Date Published:
- Journal Name:
- 2021 ASEE Virtual Annual Conference
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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The goal of our exploratory study was to examine how management and staff in engineering education making spaces are enacting equitable access amongst their users (e.g., students). We examined six different making space types categorized by Wilczynsky’s and Hoover’s classification of academic makerspaces, which considered scope, accessibility, users, footprint (size), and management and staffing. We reviewed research memos and transcripts of interviews of university makerspace staff, student staff, and leaders/administrators during two separate visits to these places that took place between 2017 and 2019. We inductively and deductively coded the data, and the findings suggested that equity of access was situational and contextual. From the results, we identified four additional considerations needed to ensure equitable access for engineering education making spaces: (a) spaces designed and operated for multiple points of student entry; (b) spaces operated to facilitate effective student making processes and pathways; (c) threats to expanded access: burdens and consequences; and (d) elevating student membership and equity through a culture of belonging. Together, the findings point toward a need for developing a more nuanced understanding of the concept of access that far supersedes a flattened definition of access to just space, equipment, and cost.more » « less
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Globally, universities have heavily invested in makerspaces. Purposeful investment however requires an understanding of how students use tools and how tools aid in engineering education. This paper utilizes a modularity analysis in combination with student surveys to analyze and understand the space as a network of student-tool interactions. The results show that a modularity analysis is able to identify the roles of different tool groupings in the space by measuring how well tool groups are connected within their own “module” and their connection to tools outside of their module. A highly connected tool in both categories is considered a hub that is critical to the network. Poorly connected tools indicate insignificance or under utilization. Makerspaces at two universities were investigated: School A with a full-time staff running the makerspace and School B run by student-volunteers. The results show that 3D printers and metal tools are hubs at School A and 3D printers, metal tools, and laser cutters are hubs at School B. School B was also found to have a higher overall interaction with all the tools in the space. The modularity analysis results are validated using two-semesters worth of student self-reported survey data. The results support the use of a modularity analysis as a way to analyze and visualize the complex network interactions occurring within a makerspace, which can support the improvement of current makerspaces and development of future makerspaces.more » « less
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Globally, universities have heavily invested in makerspaces. Purposeful investment however requires an understanding of how students use tools and how tools aid in engineering education. This paper utilizes a modularity analysis in combination with student surveys to analyze and understand the space as a network of student-tool interactions. The results show that a modularity analysis is able to identify the roles of different tool groupings in the space by measuring how well tool groups are connected within their own “module” and their connection to tools outside of their module. A highly connected tool in both categories is considered a hub that is critical to the network. Poorly connected tools indicate insignificance or under utilization. Makerspaces at two universities were investigated: School A with a full-time staff running the makerspace and School B run by student-volunteers. The results show that 3D printers and metal tools are hubs at School A and 3D printers, metal tools, and laser cutters are hubs at School B. School B was also found to have a higher overall interaction with all the tools in the space. The modularity analysis results are validated using two-semesters worth of student self-reported survey data. The results support the use of a modularity analysis as a way to analyze and visualize the complex network interactions occurring within a makerspace, which can support the improvement of current makerspaces and development of future makerspaces.more » « less
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Makerspaces have observed and speculated benefits for the students who frequent them. For example, previous studies have found that students who are involved in their campus’s makerspace tend to be more confident and less anxious when conducting engineering design tasks while gaining hands-on experience with machinery not obtained in their coursework. Recognizing the potential benefits of academic makerspaces, we aimed to capture what influences students to become involved in these spaces through a mixed-method study. A quantitative longitudinal study of students in a mechanical engineering program collected data on design self-efficacy, makerspace involvement, and user demographics through surveys conducted on freshmen, sophomores, and seniors. In this paper, the student responses from three semesters of freshmen level design classes are evaluated for involvement and self-efficacy based on whether or not a 3D modeling project requires the use of makerspace equipment. The study finds that students required to use the makerspace for the project were significantly more likely to become involved in the makerspace. These results inspired us to integrate a qualitative approach to examine how student involvement and exposure to the space are related. Using an in-depth phenomenologically based interviewing method, purposive sampling, and snowball sampling, six females, who have all made the conscious decision to engage in a university makerspace(s), participated in a three-series interview process. The interviews were transcribed and analyzed via emerging questions for categorical metrics and infographics of the student exposure and involvement in making and makerspaces. These findings are used to demonstrate 1) how students who do, or do not, seek out making activities may end up in the makerspace and 2) how student narratives resulting in high-makerspace involvement are impacted by prior experiences, classes, and friendships.more » « less
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.18260/1-2--36750
