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2012 IEEE 3rd International Conference on Cognitive Infocommunications (CogInfoCom)

DOI: 10.1109/coginfocom.2012.6422017

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Learning how to teach from "Videolectures": automatic prediction of lecture ratings based on teacher's nonverbal behavior

This paper is available in a repository.
This paper is available in a repository.

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Abstract

Large repositories of presentation recordings (e.g., “Videolectures” and “Academic Earth”) often provide their users with rating facilities. The rating of a presentation certainly depends on the content, but the way the content is delivered is likely to play a role as well. This paper focuses on the latter aspect and shows that nonverbal behavior (in particular arms movement and prosody) allows one to predict whether a presentation is rated as low or high in terms of quality. The experiments have been performed over 100 presentations collected from “Videolectures” and the accuracy is up to 66% depending on the techniques adopted. In other words, nonverbal communication actually influences the ratings assigned to a presentation.