REDES BAYESIANAS APLICADAS A SISTEMAS TUTORES INTELIGENTES

Abstract

One of the main challenges when developing an
Intelligent Tutoring System (ITS) is the individualized
treatment of the student, which is obtained mainly thought
the adaptativity of the system to each student, a complex
issue that comprises different characteristics of personality,
such as: learning style, intelligence, previous knowledge, the
history of the pupil and also the emotions. This work
encircles the issue about the adaptability of the tutoring
system to the knowledge of the pupil through a model of
student based on Bayesian Network (BNs). Considering the
level of knowledge of the student is inaccurate information,
BNs are considered suitable for environments under
uncertainty. This work intends to present the employment of
the Knowledge Acquisition Level (KAL) and the Assessment
Unit (AU) as tools for producing learning evidences thought
a BN. This work is a summary of the master theses presented
by Samuel F. Lima in 2010.

Index Terms ⎯ Education; Intelligent Tutoring System;
Bayesian Network.