Abstract:
Web-based tutoring systems are increasingly
popular due to their appeal over traditional paperbased
textbooks. Whereas many tutoring systems are
static HTML, the Bayesian intelligent tutoring system
can help a student navigate through the online
course materials, recommend learning goals, and
generate appropriate reading sequences. This paper
presents a Bayesian intelligent tutoring system for
computer programming, called BITS. The decision
making process of this system is guided by Bayesian
networks, which are a formal framework for
uncertainty management in Artificial Intelligence
based on probability theory. The primary function of
an agent is to help the user better use, manage and
interact with the computer applications. Intelligent
agents perform tasks for students as a dynamic,
personal, and smart learning environment. In
Intelligent Tutoring System, the student model has
the ability of recording information on students. With
this information, teaching and learning can proceed
in a variety of ways based on their needs and
interest.
