We present a distributed, scalable, student-driven method for both defining a set of projects and subsequently assigning students to project teams. This process has been implemented within a mixed online/in-person multi-university course comprised of both undergraduate and graduate level students who are predominantly, but not exclusively, pursuing engineering degrees. Our Innovation Based Learning (IBL) course seeks to provide students with maximum freedom and responsibility for their own learning; we seek to radically rethink and reduce the organizational tasks normally performed by the instructor. Re-assigning these tasks to the students creates new opportunities to learn soft skills such as giving an elevator pitch, project management, market research, and online collaboration. Key technology enablers used in this process are: Flipgrid for sharing short videos, and a Slack channel for both one-to-one and group chat.
All projects are defined and proposed by the students. We teach market needs analysis, and jump-start student brainstorming, by requiring that each proposal relate to a Federal Funding Opportunity Announcement (FOA). Student-proposed projects also ensure that each semester’s mix of projects addresses the unique set of backgrounds/interests of that student cohort. By democratizing the assignment of working groups, we maximize student buy-in and motivation for their topic and team. One concern with this distributed process is speed; will it take too long to crowd-source ideas and self-assemble teams? Using new digital platforms, individual student project proposals are created and reviewed entirely outside of class meeting times. Grouping students into teams is also a student-driven activity which requires minimal instructor intervention or in-class overhead. We will share considerations, surprises, and lessons-learned from this process as it has been employed and refined, over multiple years, within a multi-university IBL course. A step-by-step implementation guide is provided for others wishing to emulate the process.
Ryan Striker is a life-long learner. Ryan has over a decade of professional experience designing embedded electronic hardware for industrial, military, medical, and automotive applications. Ryan is currently pursuing a PhD in Electrical and Computer Engineering at North Dakota State University. He previously earned his MS in Systems Engineering from the University of Saint Thomas and his BS in Electrical Engineering from the University of Minnesota.
http://orcid.org/0000-0002-7257-0817
North Dakota State University
[biography]
Experienced Systems Engineer with a demonstrated history of working in the electrical and electronic manufacturing field. Highly skilled in Embedded Devices, Software Engineering, and Electronics.
Extremely motivated and self-reliant with a great believe in autonomy, new ways to solve problems and ROWE approaches. Team player and devoted to create superb working environments through dedication and team culture.
Strong information technology professional with two MSc's and working on a Doctor of Philosophy - PhD focused in Electrical Engineering from North Dakota State University.
Mary is a Ph.D. candidate in biomedical engineering with research focused in the area of bioelectromagnetics, specifically designing electronics that can be used as medical devices. She obtained her B.S. and M.S. degrees at NDSU in electrical and computer engineering. Mary is also interested in STEM education research.
http://orcid.org/https://0000-0003-3586-4266
North Dakota State University
[biography]
Lauren Singelmann is a Masters Student in Electrical and Computer Engineering at North Dakota State University. Her research interests are innovation-based-learning, educational data mining, and K-12 Outreach. She works for the NDSU College of Engineering as the K-12 Outreach Coordinator where she plans and organizes outreach activities and camps for students in the Fargo-Moorhead area.
Ellen Swartz is currently pursuing a M.S. degree in Biomedical Engineering at North Dakota State University. Her research interests include STEM education, innovation-based learning, and agent-based modeling of complex adaptive systems. She previously received her B.S. degree from North Dakota State University in Electrical and Computer Engineering.
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