Authors:
Kahina Amokrane
1
;
Domitile Lourdeaux
1
and
Georges Michel
2
Affiliations:
1
Universit de Technologie de Compiegne, France
;
2
AFPA, France
Keyword(s):
Virtual Reality, Knowledge Representation, Scenario Adaptation, Plan Recognition, Serious Game.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Bayesian Networks
;
Computational Intelligence
;
Enterprise Information Systems
;
Evolutionary Computing
;
Industrial Applications of AI
;
Knowledge Discovery and Information Retrieval
;
Knowledge Representation and Reasoning
;
Knowledge-Based Systems
;
Machine Learning
;
Soft Computing
;
Symbolic Systems
Abstract:
Virtual reality is a very interesting technology for professional training. We can mention in particular the
ability to simulate the activity without real danger, the flexibility in the informations’ presentation, or the exact
control parameters of the simulation allows to reproduc specific situations. Today, technological maturity
allows to plan increasingly a complex applications. However, in one hand, this complexity increases the
difficulty, at the same time, to propose a pedagogical and narrative control (to ensure a given learning and
narrative structure) and some freedom of actions (to promote the emergence of various, unique and suprised
situations in order to ensure a learning-by-doing/errors). In other hand, this complexity makes difficult the
tracking and understanding of learner’s path. In this paper, we propose 1- a scripting model for training virtual
environment combining both a pedagogical control and the emergence of pertinent learning situations and 2-
tracking of t
he learner’s actions, but also analysis and automatic diagnosis tools of the learner’s performances.
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