Free ticketed event
Makerspaces have proliferated on America’s college and community college campuses, with estimates citing more than 150 academic examples of 100 to more than 1,000 active student members and costs in the thousands to millions of dollars to create these spaces.
Educators argue that makerspaces democratize learning, engage students, and foster life-long learning. Research has shown that engaging in engineering makerspaces boosts students’ confidence, motivation, and technical skills. However, workshop presenters have found that a pathway into and persistence as a member of a makerspace is connected with a student’s self-confidence that they can be the expert.
What if we can design spaces to encourage persistence? Presenters have found that modeling these spaces as networks of interacting tools and students can be done through end-of-semester surveys, and that modularity and nestedness analyses can provide quantitative insights into student use of the space.
This session will share the findings of a three-year IUSE NSF grant and guide participants through data set creation, the network analysis, and interpretation of key findings. Participants can expect to be equipped with the knowledge to collect their own data to perform and interpret a similar analysis.
Attendees should bring their laptops to use the software in the session, and should download the 2022 version or more recent of MATLAB before the workshop with the “Statistics and Machine Learning Toolbox” add-on. A demonstration machine will be available.
Dr. Astrid Layton is an assistant professor at Texas A&M University in the J. Mike Walker ’66 Department of Mechanical Engineering and a Donna Walker Faculty Fellow. She received her Ph.D. in Mechanical Engineering from Georgia Institute of Technology in Atlanta, Georgia. Her research uses interdisciplinary collaborations to solve large-scale system problems, developing knowledge that supports designers and decision makers. Dr. Layton is an expert on bio-inspired systems design, with a focus on the use of biological ecosystems as inspiration for achieving sustainability and resilience in the design of complex human networks/systems/systems of systems. Examples include industrial resource networks, power grids, cyber-physical systems, supply chains, innovation processes, and water distribution networks.
Dr. Julie S. Linsey is a Professor in the George W. Woodruff School of Mechanical Engineering
at the Georgia Institute of Technological. Dr. Linsey received her Ph.D. in Mechanical Engineering
at The University of Texas. Her research area is design cognition including systematic methods and tools
for innovative design with a particular focus on concept generation and design-by-analogy. Her research
seeks to understand designers’ cognitive processes with the goal of creating better tools and approaches
to enhance engineering design. She has authored over 150 technical publications including over forty
journal papers, and ten book chapters.