Boosting E-learner’s Motivation through Identifying his/her Emotional States

  • Oussama Hamal RIME Team - LRIE Laboratory (EMI), Mohammed V University, Rabat, Morocco
  • Nour-Eddine El Faddouli RIME Team - LRIE Laboratory (EMI), Mohammed V University, Rabat, Morocco
  • Samir Bennani RIME Team - LRIE Laboratory (EMI), Mohammed V University, Rabat, Morocco
  • Moulay Hachem Alaoui Harouni Faculty of Sciences, Moulay Ismail University, Meknes, Morocco
  • Mustapha Bassiri Laboratory of Physical Chemistry of Materials, Hassan 2 University, Casablanca, Morocco
Keywords: Agent, Distance-learning, Emotional states, GMM, Motivation, SDT, Voice analysis

Abstract

The main objective of e-learning platforms is to offer a high quality instructing, training and educational services. This purpose would never be achieved without taking the students' motivation into consideration. Examining the voice, we can decide the emotional states of the learners after we apply the famous theory of psychologist SDT (Self Determination Theory). This article will investigate certain difficulties and challenges which face e-learner: the problem of leaving their courses and the student's isolation.
Utilizing Gussian blending model (GMM) so as to tackle and to solve the problems of classification, we can determine the learning abnormal status for e-learner. Our framework is going to increase the students’ motivation through utilizing the notion of agent. Furthermore, it helps to assess teacher with the learning efficiency through putting attention on the learners who have the problems to accomplish the courses' objectives.This will help educatorsto contribute to the intellectual andeducational development of their learners, to prepare them to face real-lifechallengesand to advancetheir academic careers.

Published
2021-01-13
How to Cite
Oussama Hamal, Nour-Eddine El Faddouli, Samir Bennani, Moulay Hachem Alaoui Harouni, & Mustapha Bassiri. (2021). Boosting E-learner’s Motivation through Identifying his/her Emotional States. Iraqi Journal of Science, 127-132. https://doi.org/10.24996/ijs.2021.SI.1.17