TeachBot: Towards teaching robotics fundamentals for human-robot collaboration at work
Name
PIIS2405844021016868.pdf
Description
Published version
Size
1.21 MB
Format
Unknown
Checksum (MD5)
f05f2de0e30c9ad8fab3a53279e0c91f
Author(s)
Selby, Nicholas Stearns
Ng, Jerry
Stump, Glenda S
Westerman, George
Traweek, Claire
Asada, H. Harry
Date Issued
July 2021
Journal
Heliyon
Publisher
Elsevier BV
Citation
Selby, Nicholas Stearns, Ng, Jerry, Stump, Glenda S, Westerman, George, Traweek, Claire et al. 2021. "TeachBot: Towards teaching robotics fundamentals for human-robot collaboration at work." Heliyon, 7 (7).
Version
Final published version
Abstract
The shortage of skilled workers who can use robots is a crucial issue hampering the growth of manufacturing industries. We present a new type of workforce training system, TeachBot, in which a robotic instructor delivers a series of interactive lectures using graphics and physical demonstration of its arm movements. Furthermore, the TeachBot allows learners to physically interact with the robot. This new human-computer interface, integrating oral and graphical instructions with motion demonstration and physical touch, enables to create engaging training materials. Effective learning takes place when the learner simultaneously interacts with an embodiment of new knowledge. We apply this "Learning by Touching" methodology to teach basic concepts, e.g. how a shaft encoder and feedback control work. In a pilot randomized control test with a small number of human subjects, we find suggestive evidence that Learning by Touching enhances learning effectiveness in this robotic context for adult learners. Students whose learning experience included touching the robot as opposed to watching it delivers the lessons showed gains in their ability to integrate knowledge about robotics. The "touching" group showed statistically significant gains in self-efficacy, which is an important antecedent to further learning and successful use of new technologies, as well as gains in knowledge about robotic concepts that trend toward significance.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution 4.0 International license
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1016/j.heliyon.2021.e07583
