Learning with Sociable Robots and Artifacts
Sandra Y. Okita,
Teachers College, Columbia University –
People often turn to others to improve their own learning. Technological artifacts (e.g. humanoid robots, pedagogical agents/avatars) often consist of human-like qualities ranging across appearance, behavior, and intelligence. These features often elicit a social response from humans that provide distinctive ways to examine human-artifact interactions. Virtual humans and humanoid robots create unique situations that have interesting implications for peer learning and social behavior. The talk explores possible ways to capitalize on the strong social components of technology that enables students to develop peer-learning relationships (e.g., recursive feedback during learning-by-teaching, self-other monitoring). I will introduce some ongoing research that uses technological artifacts (robots, pedagogical agents/avatars) as a threshold to learning, instruction, and assessment in formal (e.g., classrooms) and informal learning environments (e.g., online learning environments). Technological artifacts also present an array of interesting design choices (e.g., customization, creating look-alikes, adopting personas) when modeling interactions with human learners, and how identifying cause-and-
effect relationships enables us to more effectively design interventions. I will introduce work in this area that explore how facial similarity with peer avatars may influence human learning, and how robotic features combined with specific scripts and scenarios assist engagement and behavior.
Sandra Y. Okita is an Associate Professor of Technology and Education at Teachers College, Columbia University. Her work uses innovative technologies (i.e., humanoid robots, robotic systems, games for learning, pedagogical agents/avatars, virtual and mixed reality environments) as a threshold to learning, instruction, and assessment within the K-12 classroom environment and beyond. Okita comes from a cognitive science, educational technology, and human-computer interaction background from Stanford University. Much of
Okita’s work involves examining how robots and digital games can test theories about conditions for learning and facilitate collaborative learning. Her research aims to capitalize on the strong social components of technology that enables students to develop peer-learning relationships with technology in the STEM and biological science subject areas. Okita’s interdisciplinary work finds publications in both educational and computer science fields (Journal of the Learning Sciences, British Journal of Educational Technology, ACM Transactions on Interactive Intelligent Systems). Okita is an active member of International Society of the
Learning Sciences (ISLS), American Educational Research Association (AERA), ACM/IEEE International Conference on Human Robot Interaction (HRI), and a steering committee member of IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN) that highlights human-robot collaboration in relation to human learning and performance. Her work has been extensively featured in The New York Times, and the Wall Street Journal. Okita has had numerous federal and industrial grants from the National Science Foundation, Honda Research Institute, Google, Omron, and Sony.
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