Using machine learning to predict learner emotional state from brainwaves

Abstract

Intelligent Tutoring Systems (ITS) learner model has progressively evolved. Initially composed of a cognitive module it was extended with a psychological module and an emotional module. The learner model still remains non-exhaustive. Methods of data collection on the cognitive and emotional state of the learner often lack precision and objectivity. In this paper we introduce an emomental agent. It interacts with an ITS to communicate the emotional state of the learner based upon his mental state. The mental state is obtained from the learner's brainwaves. The agent learns to predict the learner's emotions by using machine learning techniques. © 2007 IEEE.