An Affective Distant Learning Model Using Avatars as User Stand-in

Abstract

Emotions play an important role in distant learning. Negative emotions are one of the main reasons of high drop-off. Real time assessment of the emotional state of the learner is complex and that complicates real time adaptation of the learning context to boost the motivation of learners. In this paper we introduce the use of avatars with facial expressions corresponding with the emotional state of the learner. Facial expressions of learners are recorded and analysed. This enables the use of personalised Avatars and emotional facial expression. The system and results of experiments are described in this paper.