Title:
Applying behavioral strategies for student engagement using a robotic educational agent
Applying behavioral strategies for student engagement using a robotic educational agent
dc.contributor.author | Brown, LaVonda | en_US |
dc.contributor.author | Kerwin, Ryan | en_US |
dc.contributor.author | Howard, Ayanna M. | en_US |
dc.contributor.corporatename | Georgia Institute of Technology. Human-Automation Systems Lab | en_US |
dc.contributor.corporatename | Georgia Institute of Technology. Mobile Robotics Lab | en_US |
dc.contributor.corporatename | Georgia Institute of Technology. Institute for Robotics and Intelligent Machines | en_US |
dc.date.accessioned | 2013-12-03T21:30:56Z | |
dc.date.available | 2013-12-03T21:30:56Z | |
dc.date.issued | 2013-10 | |
dc.description | ©2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. | en_US |
dc.description | To be published in the 2013 IEEE International Conference on Systems, Man, and Cybernetics (SMC) Manchester, UK, October 2013. | en_US |
dc.description.abstract | Adaptive learning is an educational method that utilizes computers as an interactive teaching device. Intelligent tutoring systems, or educational agents, use adaptive learning techniques to adapt to each student’s needs and learning styles in order to individualize learning. Effective educational agents should accomplish two essential goals during the learning process – 1) monitor engagement of the student during the interaction and 2) apply behavioral strategies to maintain the student’s attention when engagement decreases. This paper focuses on the second objective of reengaging students using various behavioral strategies through the utilization of a robotic educational agent. Details are provided on the overall system approach and the forms of verbal and nonverbal cues used by the robotic agent. Results derived from 24 students engaging with the robot during a computer-based math test show that, while various forms of behavioral strategies increase test performance, combinations of verbal cues result in a slightly better outcome. | en_US |
dc.identifier.isbn | 978-1-4244-0652-9 | |
dc.identifier.uri | http://hdl.handle.net/1853/49757 | |
dc.language.iso | en_US | en_US |
dc.publisher | Georgia Institute of Technology | en_US |
dc.publisher.original | Institute of Electrical and Electronics Engineers | en_US |
dc.subject | Social robotics | en_US |
dc.subject | Educational agents | en_US |
dc.subject | Engagement | en_US |
dc.title | Applying behavioral strategies for student engagement using a robotic educational agent | en_US |
dc.type | Text | |
dc.type.genre | Proceedings | |
dc.type.genre | Post-print | |
dspace.entity.type | Publication | |
local.contributor.author | Howard, Ayanna M. | |
local.contributor.corporatename | School of Civil and Environmental Engineering | |
local.contributor.corporatename | Institute for Robotics and Intelligent Machines (IRIM) | |
relation.isAuthorOfPublication | 6d77e175-105c-4b0b-9548-31f20e60e20a | |
relation.isOrgUnitOfPublication | 88639fad-d3ae-4867-9e7a-7c9e6d2ecc7c | |
relation.isOrgUnitOfPublication | 66259949-abfd-45c2-9dcc-5a6f2c013bcf |
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