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Learner Attitudes Towards Humanoid Robot Tutoring Systems

Maya Dimitrova, Hiroaki Wagatsuma, Gyanendra Nath Tripathi, Guangyi Ai

Year
2019
Citations
13

Abstract

A novel framework for investigation of the learner attitude towards a humanoid robot tutoring system is proposed in the chapter. The theoretical approach attempts to understand both the cognitive motivation as well as the social motivation of the participants in a teaching session, held by a robotic tutor. For this aim, a questionnaire is delivered after the eye tracking experiment in order to record the type and amount of the learned material as well as the social motivation of the participants. The results of the experiments show significant effects of both cognitive and social motivation influences. It has been shown that cognitive motivation can be observed and analyzed on a very individual level. This is an important biometric feature and can be used to recognize individuals from patterns of viewing behaviors in a lesson. Guidelines, drawn from first-person accounts of learner participation in the study, are also formulated for achieving more intuitive interactions with humanoid robots intended to perform social jobs like being teachers or advisors.

Keywords

Humanoid robotTUTORPsychologySession (web analytics)CognitionSocial robotHuman–computer interactionIntrinsic motivationComputer scienceCognitive psychology

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