Virtual Conference
July 26, 2021
July 26, 2021
July 19, 2022
Multidisciplinary Engineering
27
10.18260/1-2--37338
https://peer.asee.org/37338
519
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.
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.
Lauren Singelmann is a PhD 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.
Enrique is an 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. He is a 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.
Stanley Ng received his BS in Biomedical Engineering from University of California Irvine and MS in Biomedical Diagnostics from Arizona State University. He serves as faculty and director of engineering programs at Biola University. Currently, he is pursuing a Ph.D. in Engineering and STEM Education at North Dakota State University.
This paper evaluates the use of an Innovative Impact Scale (IIS) alongside Webb’s Depth of Knowledge (DoK) as metrics for student assessment within an Innovation-Based Learning (IBL) course. The IBL model provides students with the freedom and responsibility to choose and direct their own learning while encouraging innovative thinking through collaborations that are both multidisciplinary and multi-institutional. Through these collaborations, students determine a current societal challenge and are expected to contribute their individual knowledge and skills towards finding an innovative solution. Within the IBL model, student assessment is not performed via the traditional methods of homework or exams. Instead, students are evaluated on their ability to relate and apply core course concepts towards a team innovation that introduces novelty.
This Innovation-Based Learning model has been implemented within a cardiovascular engineering course for its third consecutive semester and is currently offered across four institutions. The diversity of the participating universities and the enrolled students (both undergraduate and graduate) fosters an environment for innovative thinking. However, being an innovative multidisciplinary course creates difficulties when evaluating students on their course outcomes. Based on their individual backgrounds and skills, each student creates learning objectives that are unique and personalized while also contributing to their team’s innovation project. With such diversity of student work, applying a single grading rubric is impractical. Another problem occurs in evaluating the innovation itself. How can instructors consistently rank the novelty and value of such diverse student work? To tackle these problems, a grading scheme that involves multiple expert assessments of both the value and the impact of a student’s innovation needed to be developed.
This work presents and describes the development of the Innovative Impact Scale and how it has been integrated alongside Webb’s Depth of Knowledge levels as metrics to assess the innovative learning outcomes of students enrolled in an IBL course. Data on student learning outcomes collected from the course’s online platform will be assessed. To determine the effectiveness of using the IIS alongside Webb’s DoK as an assessment tool, multiple instructors from the institutions involved will review student learning outcomes. Instructor reviews will be assessed to compute inter-rater agreement scores, with instances producing the strongest agreements and disagreements evaluated and results discussed.
Swartz, E. M., & Striker, R., & Singelmann, L., & Alvarez Vazquez, E., & Pearson, M., & Ng, S. S. (2021, July), Innovating Assessment: Using Innovative Impact as a Metric to Evaluate Student Outcomes in an Innovation-Based Learning Course Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--37338
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