2023 ASEE Annual Conference & Exposition

How Does Students’ Use of Speech Ground and Embody Their Mechanical Reasoning during Engineering Discourse?

Presented at Disciplinary Engineering Education Research – Session 1

This full paper concerns an exploratory study that investigates students’ reasoning about torsion. Mechanical reasoning is critical to engineering applications and yet students still struggle to accurately predict, analyze, and model mechanical systems using formal symbolic notations (i.e., formalizations). To understand the nature of students’ reasoning, we analyzed students’ discourse to explore two competing hypotheses: (H1) The Formalisms First (FF) hypothesis that students report their mechanical reasoning predominantly using mathematical formalisms that take on a disembodied, allocentric (observer) point-of-view; or (H2) the Grounded and Embodied Cognition (GEC) hypothesis that students predominantly use independent speech which includes analogy and imagery to simulate the physical structure and function of an object(s) using an embodied, egocentric (first-person) point-of-view in addition to an allocentric point-of-view. Qualitative results from discourse analysis of two student dyads showed that students’ mechanical reasoning revealed through their speech included both analogy and imagery, as predicted by H2. Students generated analogies and imagery that described dynamic behaviors, such as how torque caused displacement, stored and released energy, and fractured. Usage of analogies and imagery supports that students’ mechanical reasoning often drew upon simulations of torsion-related sensorimotor experiences. Students’ egocentric and allocentric imagery invoked sensorial experiences in their speech, with allocentric viewpoints being more common, as predicted by H1 and H2. Student discourse included many references to formalisms, also consistent with the H1. Data from students’ verbal discourse on mechanical reasoning suggests they employ both GEC and FF viewpoints of torsion, which has implications for designing effective learning experiences and for assessing students’ knowledge.

Authors

Matthew M. Grondin University of Wisconsin - Madison [biography]

Matthew is a graduate student completing a joint-degree in the Departments of Mechanical Engineering and Educational Psychology-Learning Sciences at the University of Wisconsin-Madison. His research revolves around application of embodied learning in engineering education with a primary focus on assessments that bring equitable and inclusive practices to the diverse population of engineering undergraduate students. Matthew has been nominated for numerous teacher awards including Early Excellence in Teaching, Innovation in Teaching, and Honored Instructor. His kind nature and consideration brings connection, community, and ongoing mentorship for his students.
Michael I. Swart University of Wisconsin - Madison [biography]

Michael is an artist and musician masquerading as an academic, honored with the opportunity to research and design educational technologies that engage the body and the mind to make learning fun and productive.
Arushi Renschler Pandey University of Wisconsin-Madison [biography]

Arushi is a 4th year undergraduate student in the Department of Electrical Engineering. Her research interests include how engineering students use metaphor and imagery when mechanically reasoning about engineering phenomena, and how recognition of students' individual ways of verbalizing knowledge can enrich assessment practices in engineering education.
Dr. Katherine Fu University of Wisconsin - Madison [biography]

Dr. Kate Fu is the Jay and Cynthia Ihlenfeld Associate Professor of Mechanical Engineering at the University of Wisconsin-Madison. From 2014 to 2021, she was an Assistant and Associate Professor of Mechanical Engineering at Georgia Institute of Technology. Prior to these appointments, she was a Postdoctoral Fellow at Massachusetts Institute of Technology and Singapore University of Technology and Design (SUTD). In May 2012, she completed her Ph.D. in Mechanical Engineering at Carnegie Mellon University. She received her M.S. in Mechanical Engineering from Carnegie Mellon in 2009, and her B.S. in Mechanical Engineering from Brown University in 2007. Her work has focused on studying the engineering design process through cognitive studies, and extending those findings to the development of methods and tools to facilitate more effective and inspired design and innovation. Dr. Fu is a recipient of the NSF CAREER Award, the ASME Design Theory and Methodology Young Investigator Award, the ASME Atlanta Section 2015 Early Career Engineer of the Year Award, and was an Achievement Rewards For College Scientists (ARCS) Foundation Scholar.
Prof. Mitchell Nathan University of Wisconsin - Madison [biography]

Mitchell J. Nathan is a professor of learning sciences in the Department of Educational Psychology at the University of Wisconsin-Madison. Prof. Nathan received his Ph.D. in experimental (cognitive) psychology. He also holds a B.S. in electrical and computer engineering, mathematics and history. He has worked in research and development in artificial intelligence, computer vision and robotic mobility, including: design and development of autonomous robotic arms and vehicles; sensor fusion; the development of expert systems and knowledge engineering interview techniques; and the representation of perceptual and real-world knowledge to support inference-making in dynamic environments. Nathan also has worked on computer-based tutoring environments for mathematics education that rely heavily on students' own comprehension processes for self-evaluation and self-directed learning (so-called unintelligent tutoring systems). Prof. Nathan has authored over 100 peer-reviewed publications, given more than 120 presentations at professional meetings, and has secured over $25M in research funds to investigate and improve STEM learning, reasoning and instruction. Among his projects, Dr. Nathan directed the IERI-funded STAAR Project, which studied the transition from arithmetic to algebraic reasoning, served as Co-PI for the NSF-funded AWAKEN Project, which documented how people learn and use engineering, and currently co-directs the National Center for Cognition and Mathematics Instruction. He is a faculty member for the Latin American School for Education, Cognitive and Neural Sciences. As part of his service to the nation, Dr. Nathan served on the National Academy of Engineering/National Research Council Committee on Integrated STEM Education, and is currently a planning committee member for the Space Studies Board of the National Academy of Sciences/National Research Council workshop Sharing the Adventure with the Student: Exploring the Intersections of NASA Space Science and Education. At the University of Wisconsin, Dr. Nathan holds affiliate appointments in the Department of Curriculum & Instruction, the Department of Psychology, and the Wisconsin Center for Education Research. He is a member of the steering committee for the Delta Program (part of the national CIRTL Network), which promotes the development of a future national STEM faculty committed to implementing and advancing effective teaching practices for diverse student audiences. Prof. Nathan currently is Director of the Center on Education and Work and Director of the Postdoctoral Training Program in  Mathematical Thinking, Learning, and Instruction. He is an inductee and executive board member of the University of Wisconsin’s Teaching Academy, which promotes excellence in teaching in higher education.

Download paper (1.03 MB)

Are you a researcher? Would you like to cite this paper? Visit the ASEE document repository at peer.asee.org for more tools and easy citations.

» Download paper

« View session