ABSTRACT
For the purpose of improving the quality in Elearning process and overcoming the limitations of the current online educational environments, we propose to take into consideration the emotional states of students during Elearning sessions. Our objective is to ensure the ability of emotional intelligence: Emotion Recognition, in an eLearning environment. Thus, we present an architecture of Emotionally Intelligent Elearning System (EIES). Within the development of a computational probabilistic model of emotions, we proposed a Bayesian Network (BN) model to deal with emotions in Elearning environments and handle the uncertain nature of emotion recognition process. In a second phase, we focus on the incorporation of the emotion recognition in the Elearning systems by developing a simulation of EIES based on the BN model, able to predict the students’ affects. Consequently, we reached positive and promising results related to the fact that simulated EIES based on the BN model of emotions predicts correctly the student’s emotion when an event occurs during an Elearning session.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes on contributors
Thouraya Daouas PhD from University of Neuchâtel, Switzerland. Researcher, teacher in Computing and management at HEC of Carthage (www.ihec.rnu.tn). Academic Dean there during 2016–2017. Main research subjects: eLearning, Machine Learning, Self-Regulated Learning and Dynamic Adaptive Hypermedia. Insures several Hybrid and Distance mode courses. Supervises works of the Masters and thesis in Computing and in Management and Strategy.
Hanen Lejmi PhD Student in Higher Institute of Management of Tunis. Teacher of computer sciences in English in a pioneer middle school. Research interests: Multi-agent modeling and simulation, Organizational Psychology and Affective computing.
ORCID
Thouraya Daouas http://orcid.org/0000-0002-6469-246X
Hanen Lejmi http://orcid.org/0000-0002-3409-1225