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Rule-based detection of emotions in the Khan Academy platform

Leony, Derick and Muñoz-Merino, Pedro J. and Pardo, Abelardo and Ruipérez-Valiente, José A. and Arellano Martín-Caro, David and Delgado Kloos, Carlos (2014) Rule-based detection of emotions in the Khan Academy platform. In: International Workshop on Massive Open Online Courses, 15 -16 May 2014, Antigua, Guatemala.

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The current relevance of Massive Open Online Courses (MOOCs) has provoked researchers in educational technology to work towards improving their pedagogical outcomes. Adaptive MOOCs are an example within this context. Given the importance of affective information within the adaptive systems, we propose a set of models to detect four emotions known to correlate with learning gains. The implementation of the models and the initial results from its application in a case study dataset are also provided.

Item Type: Conference or Workshop Papers (Paper)
Uncontrolled Keywords: MOOCs, emotion detection, user modeling, learning analytics.
Depositing User: Jose Antonio Ruiperez
Date Deposited: 30 Jan 2015 11:28
Last Modified: 20 Jun 2016 09:53

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