Guy Gouardères

The Affective Tutoring System

Affective Computing is a new Artificial Intelligence area that deals with the possibility of making computers able to recognize human emotions in different ways. This paper represents a study about the integration of this new area in the intelligent tutoring system. We argue that socially appropriate affective behaviors would provide a new dimension for collaborative learning systems. The main goal is to analyses learner facial expressions and show how Affective Computing could contribute for this interaction, being part of the complete student tracking (traceability) to monitor student behaviors during learning sessions.

An Actor Based Architecture for Intelligent Tutoring Systems

The evolution of intelligent tutoring systems (ITS) toward the use of multiple learning strategies calls on a multi-agent architecture. We designed an ITS where several agents assume different pedagogical roles; consequently, we called them actors. We first describe the conceptual architecture of an actor which allows it to be reactive, instructable, adaptive and cognitive. We then provide a detailed view of this architecture and show how it functions with an example involving the different actors of a new learning strategy, the learning by disturbing strategy.

LANCA: A Distance Learning Architecture Based on Networked Cognitive Agents

The use of Internet as a general vehicle to support distance learning is a recent orientation of learning with multiple positive and negative consequences. The important disadvantage of such an approach is to forget the difference between information and knowledge, between consultation and pedagogy, leading to poor training as a consequence. The need of providing access to information to a larger number of people should not be realized to the detriment of the quality of training. In this paper we first explain why and how ITS techniques using intelligent agents can be adapted to distance learning. We precise the main characteristics of these agents and their functions in a distributed environment. We then present the architecture of this environment with the role of the different intelligent agents. We show, on an example, how the agents interact with the learner and particularly how a pedagogical agent can switch to a new strategy according to the progression of the learner.

ONTOLOGY-BASED USER MODELING AND E-PORTFOLIO GRID LEARNING SERVICES

Several challenges need to be met by a new generation of learning services. On one hand, they need to fit into a ubiquitous and serendipitous learning vision, to adapt to different types of users with different backgrounds and needs. On the other hand, they need to integrate modern pedagogical approaches of learning. These services will probably rely on the cooperation of different distributed, autonomous, goal-oriented entities, and they can be Grid- or Web-Oriented. In this paper, we show how core technologies can contribute to the development of a next generation of learning services. In particular, we focus our attention on personalized services delivery for learning by employing an ontological perspective and user modeling techniques. This paper presents some preliminary results obtained within Elegi FP6 project.

Agent-based collaborative affective e-learning system

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 learners 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).

E-Portfolio to Promote the Virtual Learning Group Communities on the Grid

In Vocational and Educational Training (VET), new trends are toward social learning and, more precisely, toward informal learning. In such settings, this article introduces a process — the e-Qualification — to manage informal learning on the ELeGI “Learning Grid Infrastructure.†It argues that this process must occur in a social context, such as virtual communities. On the one hand, it describes their necessary characteristics and proprieties that lead to the creation of a new kind of virtual community: the Virtual Learning Grid Community (VLGC). On the other hand, e-Qualification cannot occur without the help of a kind of user’s profile, called e-portfolio. Moreover, the e-portfolio is also a process, used to manage the Virtual Learning Grid Communities. The e-Qualification and Virtual Learning Grid Communities’ management will probably rely on the cooperation of different distributed, autonomous, goal-oriented entities, called Mobile Peer-to-Peer (P2P) Agents. Furthermore, we hope that implementing these services will decrease the lack of informal learning treatment on the grid and will become the basis for new services on the Learning Grid.

Workshop on Social and Emotional Intelligence in Learning Environments

It has been long recognised in education that teaching and learning is a highly social and emotional activity. Students’ cognitive progress depends on their psychological predispositions such as their interest, confidence, sense of progress and achievement as well as on social interactions with their teachers and peers who provide them (or not) with both cognitive and emotional support. Until recently the ability to recognise students’ socio-affective needs constituted exclusively the realm of human tutors’ social competence. However, in recent years and with the development of more sophisticated computer-aided learning environments, the need for those environments to take into account the student’s affective states and traits and to place them within the context of the social activity of learning has become an important issue in the domain of building intelligent and effective learning environments. More recently, the notion of emotional intelligence has attracted increasing attention as one of tutors’ pre-requisites for improving students’ learning.

Some Tasks of Intelligent Tutoring Systems Design for Civil Aviation Pilots

This article aims to consider the essential problems related to the design of innovative intelligent tutoring systems based on multi-agent technologies. Amongst others, these are: problems of elaboration of structure for such systems and of algorithms of agents behaviour, problems of creation of training object’s models and their verification, problems of organisation of structural and functional relations between all elements of training system. All these problems are considered in the framework of application to intelligent tutoring systems for civil aviation pilots.

Workshop II - Pedagogical Agents

This workshop will bring together researchers having different conception of the notion of an agent. It will particularly focus on how these notions have growth to reach the needs of Intelligent Tutoring Systems in student modeling, multi-agents learning environments, collaborative learning, animated agents, multi modal interfaces, personality, emotions and animated characters, empirical evaluation of agents-based environments. It will focus on the following questions.

Towards Qualitative Accreditation with Cognitive Agents

This paper presents the results of application of cognitive models to aeronautic training through the usage of a multi-agent based ITS (Intelligent Tutoring Systems). More particularly, the paper deals with models of human error and application of multi-agent technologies to diagnose human errors and underlying cognitive gaps. The model of reasoning based on qualitative simulation supplies a wide variety of parameters as the base for pedagogical evaluation of the trainee. The experimental framework is simulation-based ITS, which uses a ≪learning by doing errors≫ approach. The overall process is intended to be used in the perspective of e-accreditation of training, which seems to become unavoidable in the context of globalisation and development of e-learning in aeronautic companies.