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Board 153: Continued Assessment of i-Newton for the Engaged Learning of Engineering Dynamics

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Conference

2019 ASEE Annual Conference & Exposition

Location

Tampa, Florida

Publication Date

June 15, 2019

Start Date

June 15, 2019

End Date

June 19, 2019

Conference Session

NSF Grantees Poster Session

Tagged Topic

NSF Grantees Poster Session

Page Count

10

DOI

10.18260/1-2--32271

Permanent URL

https://strategy.asee.org/32271

Download Count

66

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Paper Authors

biography

Rachel Vitali University of Michigan

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Rachel Vitali is a doctoral candidate in the Mechanical Engineering department at the University of Michigan, where she also received her B.S.E. in 2015 and M.S.E in 2017. Her research interests include computational and analytical dynamics with applications to wearable sensing technology for analysis of human motion in addition to incorporating technology into undergraduate courses for engaged learning.

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Noel C. Perkins University of Michigan

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Noel Perkins is the Donald T. Greenwood Collegiate Professor of Engineering and an Arthur F. Thurnau Professor in Mechanical Engineering at the University of Michigan. He earned his PhD at U. C. Berkeley in 1986 (Mechanical Engineering) prior to joining the faculty at Michigan. His research interests draw from the fields of computational and nonlinear dynamics with applications to the mechanics of single molecule DNA and DNA/protein complexes, wireless inertial sensors for analyzing human motion, and structural dynamics, topics on which he has published over 150 publications in archival journals and conference proceedings.

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Cynthia J. Finelli University of Michigan Orcid 16x16 orcid.org/0000-0001-9148-1492

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Dr. Cynthia Finelli is Associate Professor of Electrical Engineering and Computer Science, Associate Professor of Education, and Director and Graduate Chair for Engineering Education Research Programs at University of Michigan (U-M). Dr. Finelli is a fellow in the American Society of Engineering Education, a Deputy Editor of the Journal for Engineering Education, an Associate Editor of the IEEE Transactions on Education, and past chair of the Educational Research and Methods Division of ASEE. She founded the Center for Research on Learning and Teaching in Engineering at U-M in 2003 and served as its Director for 12 years. Prior to joining U-M, Dr. Finelli was the Richard L. Terrell Professor of Excellence in Teaching, founding director of the Center for Excellence in Teaching and Learning, and Associate Professor of Electrical Engineering at Kettering University.

Dr. Finelli's current research interests include student resistance to active learning, faculty adoption of evidence-based teaching practices, the use of technology and innovative pedagogies on student learning and success, and the impact of a flexible classroom space on faculty teaching and student learning. She also led a project to develop a taxonomy for the field of engineering education research, and she was part of a team that studied ethical decision-making in engineering students.

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Abstract

This study, which is funded by NSF’s DUE:EHR program, documents the use of inertial measurement units (IMUs) as an engaged learning exercise (called i-Newton) in an otherwise traditionally taught introductory dynamics course. The vast majority of dynamics courses do not include opportunities for hands-on investigations of the engineering dynamics derived and studied in class, and this exercise represents an intervention to a teaching pedagogy that historically only passively engages students in their learning of dynamics concepts.

There is ample evidence showing that students who see difficult theoretical concepts in action and engage in hands-on learning of those concepts are more likely to understand the abstract nature of the movements. Thus, integrating hands on investigations into the introductory dynamics course is likely to improve student learning. However, as the course is often a required prerequisite for multiple upper level classes and, as a result, typically has quite large enrollments, a traditional hands-on laboratory can be difficult to implement Given the ease with which IMUs yield motion data (kinematic data), they provide a scalable, ready-made platform to explore and learn engineering dynamics. We hypothesize that using IMU-based, hands-on experiments in the engineering dynamics course will increase conceptual understanding, engineering self-efficacy, and intention to persist.

The study is conducted in the context of an undergraduate introductory dynamics course required by several different engineering disciplines at a large public university. We systematically incorporate the IMU-based experiments into the class at three levels: 1) demonstrations, 2) prescribed experiments, and 3) student projects. The Dynamics Concept Inventory, a validated instrument covering 14 commonly misunderstood and/or important engineering dynamics concepts, is used to measure changes in conceptual understanding. Another validated instrument, the Longitudinal Assessment of Engineering Self-Efficacy (LAESE), is used to measure changes in engineering self-efficacy, course-specific self-efficacy, and intention to persist. The DCI and LAESE are administered online at the beginning and end of the term for modest extra credit.

To date, we have collected control data from 151 students across 3 sections in 1 semester with no IMU-based experiments. We have also completed the first level of our study (362 students across 7 sections in 2 semesters) in which instructors conducted two demonstrations relating to commonly misunderstood DCI concepts and students completing assignments exploring those concepts using data provided by IMUs. The second level of our study (prescribed experiments the students conduct outside of class with IMUs supplied to them) will be complete at the end of December 2018. And level 3 (student projects) will be implemented during Spring term of 2019. Preliminary DCI results show that Level 1 and Level 2 have limited impact on student conceptual understanding as compared to the control group. Preliminary LAESE results are inconclusive regarding self-efficacy and intention to persist as compared to the control group. This update will compare the results of this first and second levels of the study against the control data.

Vitali, R., & Perkins, N. C., & Finelli, C. J. (2019, June), Board 153: Continued Assessment of i-Newton for the Engaged Learning of Engineering Dynamics Paper presented at 2019 ASEE Annual Conference & Exposition , Tampa, Florida. 10.18260/1-2--32271

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