Agent-based Collaborative Affective E-learning System

M. Ben Ammar; Adel M.Alim; Mahmoud Neji; Guy Gouardères

1st Intenational ICST Conference on Immersive Telecommunications & Workshops

Research Article

Agent-based Collaborative Affective E-learning System

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@INPROCEEDINGS{10.4108/ICST.IMMERSCOM2007.2090,
    author={M. Ben Ammar and Adel M.Alim and Mahmoud Neji and Guy Gouard\'{e}res},
    title={Agent-based Collaborative Affective E-learning System},
    proceedings={1st Intenational ICST Conference on Immersive Telecommunications \& Workshops},
    proceedings_a={IMMERSCOM},
    year={2010},
    month={5},
    keywords={Affective communication virtual environments virtual entities affective states e-learning systems},
    doi={10.4108/ICST.IMMERSCOM2007.2090}
}

M. Ben Ammar
Adel M.Alim
Mahmoud Neji
Guy Gouardères
Year: 2010
Agent-based Collaborative Affective E-learning System
IMMERSCOM
ICST
DOI: 10.4108/ICST.IMMERSCOM2007.2090

M. Ben Ammar¹^,*, Adel M.Alim¹^,*, Mahmoud Neji²^,*, Guy Gouardères³^,*

1: REsearch Group on Intelligent Machines (REGIM), University of Sfax, ENIS P.O.Box. W-3038 – Sfax – Tunisia
2: Faculté des Sciences Economiques et de Gestion, University of Sfax, –Tunisia
3: LIUPPA, IUT de Bayonne – Université de Pau et des Pays de l'Adour 64115 Bayonne, France

*Contact email: ben_ammar@acm.org, adel.alimi@ieee.org, Mahmoud.Neji@fsegs.rnu.tn, Guy.gouarderes@iutbayonne.univ-pau.fr

Abstract

In order to promote a more dynamic and flexible communication between the learner and the system, we integrate five kinds of adaptive agents in emotional framework. We focus on human facial characteristics to develop general-purpose agents that can recognize human emotion and create emotional framework with the implications of peer-to-peer technology. Emotions play an important role in cognitive processes and specially in learning tasks. Online learning is no exception. Detecting a learner’s emotional reaction for a given situation is an essential element for every e-learning system. In this paper a system for identifying facial expressions by using facial features is presented, it can recognizes 6 basic emotional expressions (happiness, sadness, surprise, fear, anger, and disgust).

Keywords: Affective communication virtual environments virtual entities affective states e-learning systems

Published: 2010-05-16
Modified: 2011-08-23

: http://dx.doi.org/10.4108/ICST.IMMERSCOM2007.2090