In this paper, we will present an educational game that we developed
in order to teach a chemistry lesson, namely drawing a Lewis diagram. We also
conducted an experiment to gather data about the cognitive and emotional
states of the learners as well as their behaviour through out our game
by using three types of sensors (electroencephalography,eye tracking, and facial
expression recognition with an optical camera)
.
Primary results show that a machine learning model (logistic regression)
can predict with some success whet her the learner will give a correct or a wrong
answer to a task presented in the game, and paves the way for an adaptive version
of the game. This latter will challenge or assist learners based on some features
extracted from our data in order to provide real-time adaptation specific to the user
Références (1) :
Alvarez, J. and L. Michaud (2008). Serious Games: Advergaming, edugaming, training and more IDATE