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dc.contributor.authorMuldner, Kasia
dc.contributor.authorGirotto, Victor
dc.contributor.authorLozano, Cecil
dc.contributor.authorBurleson, Winslow
dc.contributor.authorWalker, Erin A.
dc.identifier.citationMuldner, K., Girotto, V., Lozano, C., Burleson, W., & Walker, E. A. (2014). The Impact of a Social Robot’s Attributions for Success and Failure in a Teachable Agent Framework. In Joseph L. Polman, Eleni A. Kyza, D. Kevin O'Neill, Iris Tabak, William R. Penuel, A. Susan Jurow, Kevin O'Connor, Tiffany Lee, and Laura D'Amico (Eds.). Learning and Becoming in Practice: The International Conference of the Learning Sciences (ICLS) 2014. Volume 1. Colorado, CO: International Society of the Learning Sciences, pp. 278-285.en_US
dc.description.abstractTeachable agents foster student learning by employing the learning by teaching paradigm. Since social factors influence learning from this paradigm, understanding which social behaviors a teachable agent should embody is an important first step for designing such an agent. Here, we focus on the impact of causal attributions made by a teachable agent. To obtain data on student perceptions of agent attributions, we conducted a study involving students interacting with a social robot that made attributions to ability and effort, and to the student, itself, or both. We analyzed data from semi-structured interviews to understand how different attributions influence student perceptions, and discuss design opportunities for manipulating these attributions to improve student motivation.en_US
dc.publisherBoulder, CO: International Society of the Learning Sciencesen_US
dc.titleThe Impact of a Social Robot’s Attributions for Success and Failure in a Teachable Agent Frameworken_US
dc.typeBook chapteren_US
Appears in Collections:ICLS2014

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