2023 ASEE Annual Conference & Exposition

This work-in-progress paper aims to document the impacts of active learning
in the form of hands-on exploration on students’ conceptual understanding of
fundamental robotics dynamics concepts and motivation to learn the material.
Active learning is well-known to have noteworthy and largely positive impacts
on cognitive gains of undergraduate students in engineering (as well as many
other disciplines). Freeman et al. (2014) described the power of active learn-
ing as, ”If the experiments analyzed here had been conducted as randomized
controlled trials of medical interventions, they may have been stopped for ben-
efit—meaning that enrolling patients in the control condition might be discon-
tinued because the treatment being tested was clearly more beneficial.” Much
of engineering practice relies on visual cues, meaning strong spatial perception,
reasoning, and visualization skills are often key to success in many engineering
careers. These skills are especially true for engineering practice related to the
design and operation of robotic automated manufacturing systems. Thus, it is
crucial for students to have hands-on (active learning) experiences to fully grasp
and appreciate the complexities of operating and controlling a three-dimensional
robotic arms that might have multiple degree of freedom.

This active learning activity will be introduce into a Mechanical Engineering
technical elective course called ME:4140 - Modern Robotics and Automation,
which is offered every spring semester at the University of Iowa. The class
introduces students to the basics of robotics and automation principles, the
most relevant of which to this work are the topics covering robotic motion and
kinematics. Bi-weekly hands-on laboratories will covered spatially relevant top-
ics like rotation matrices, forward/inverse kinematics, rigid body motions, and
other concepts through in person laboratories and using robot simulators. The
timing of these laboratories is such that the material covered in the laboratories
is related to the upcoming assignment due. For assessment, surveys will be
distributed at the beginning and end of each laboratory that consists of Likert-
scale questions probing student motivation as well as self-reported homework
assignment scores to capture their level of conceptual understanding.

This paper will first describe the hands-on laboratories that will be designed
and implemented in ME:4140 during the Spring 2023 semester. Preliminary
results for student motivation and student conceptual understanding will also be
included. Implications for this work include insights into how student motivation
and learning are positively influenced by hands-on exploration. Future work
includes an investigation into the transferability of results to other robotics
contexts so instructors can implement similar activities in their courses.