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dc.contributor.authorSelby, Nicholas Stearns
dc.contributor.authorNg, Jerry
dc.contributor.authorStump, Glenda S
dc.contributor.authorWesterman, George
dc.contributor.authorTraweek, Claire
dc.contributor.authorAsada, H. Harry
dc.date.accessioned2021-12-13T20:57:13Z
dc.date.available2021-12-13T18:07:33Z
dc.date.available2021-12-13T20:57:13Z
dc.date.issued2021-07
dc.identifier.urihttps://hdl.handle.net/1721.1/138455.2
dc.description.abstractThe 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.en_US
dc.language.isoen
dc.publisherElsevier BVen_US
dc.relation.isversionof10.1016/j.heliyon.2021.e07583en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceElsevieren_US
dc.titleTeachBot: Towards teaching robotics fundamentals for human-robot collaboration at worken_US
dc.typeArticleen_US
dc.identifier.citationSelby, 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).en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.relation.journalHeliyonen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2021-12-13T18:05:16Z
dspace.orderedauthorsSelby, NS; Ng, J; Stump, GS; Westerman, G; Traweek, C; Asada, HHen_US
dspace.date.submission2021-12-13T18:05:18Z
mit.journal.volume7en_US
mit.journal.issue7en_US
mit.licensePUBLISHER_CC
mit.metadata.statusPublication Information Neededen_US


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