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Identifying Task Engagement: Towards Personalised Interactions with Educational Robots

Lee J. Corrigan, Christopher Peters, Ginevra Castellano

Year
2013
Citations
14

Abstract

The focus of this project is to design, develop and evaluate a new computational model for automatically detecting change in task engagement. This work will be applied to robotic tutors to enhance and support the learning experience, enabling timely pedagogical and empathic intervention. This work is intended to forward the current state of the art by 1) exploring how to automatically detect engagement with a learning task, 2) designing and developing new approaches to machine learning for adaptive platform-independent modelling and 3) evaluation of its effectiveness for building and maintaining learner engagement across different tutor embodiments, for example a physical and virtual embodiment.

Keywords

Computer scienceTUTORTask (project management)RobotHuman–computer interactionFocus (optics)Work (physics)Task analysisArtificial intelligenceEngineering

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