Towards a Multi-modal Emotion-Awareness e-Learning System

Abstract

This paper describes an innovative e-Learning project proposal, named MeToo, aiming to enhance existing e-learning platforms by developing tools and services which support the detection and representation of learners' emotions, as well as emotion-based learning adaptation and affective feedback. To this end, MeToo applies novel emotion detection models to rich multimodal data collected using state of the art channels, advanced sensors and novel adaptive interfaces. Via multiple small-scale pilots in formal, informal and workplace learning environments, MeToo system will intend to demonstrate a positive impact of emotion-aware e-learning on decreasing learners drop-out rates, increasing satisfaction and improving learning performance, thus making learning as a whole a better experience. MeToo's approach requires a multi discipline perspective with expertise in e-learning, software development, internet of things, educational psychology, affective sciences, social sciences and neuroscience. To this end, MeToo not only includes experts in the above domains but also specialists with access to primary and secondary schools, university students, corporate learners and open education users. The paper shows the most relevant aspects of the scientific approaches of this project proposal submitted to the Horizon 2020 ICT program of the European Commission.