Predicting Learner Answers Correctness through Brainwaves Assesment and Emotional Dimensions

We want to explore the relation between affective states, brainwaves and the learner answers during a multi-choice test questions. 24 participants were used in our experiment. While we were measuring their brainwaves, we asked them to answer 35 questions related to the 7 texts they read, for the first time, the day before. During the experiment, the participants can rate, at any time, their emotional dimensions (pleasure, arousal and dominance) on the Self-Assessment Manikin scale (SAM). Measuring the brainwaves determines the learner mental state and the emotional dimensions indicate the learner affective state. When a participant answers, he mentions if he knows the answer or not. Each answer can be either Right or False. The hypothesis of this paper is: “We can predict the learner’s answers from his emotional dimensions and his brainwaves”. By using some machine learning techniques, we reached 90.49% accuracy. In a future work, these results will be implemented in an agent to improve the pedagogical strategies and the adaptation of the content within an Intelligent Tutoring System (STI).