Abstract
Most of the current intelligent tutoring systems (ITSs) for programming focus on teaching students the syntax of a programming language as opposed to application. The main tutoring approach is to present a problem specification for the student to solve and followed by analysis of the solution with various feedbacks. Existing ITSs suffer from static domain knowledge and are restricted to the tutoring session. Therefore, this research proposes the development of a Web-based ITS to teach the application of C++ Standard Template Library (STL) to problem solving. It is discovered that students find the C++ STL difficult due to their weaknesses in understanding various object-oriented concepts. Subsequently, the dynamic domain knowledge of the C++ STL Tutor is modeled in a 2-level hierarchical structure based on pre-requisites. Bayesian network is applied to model the student's knowledge and direct the tutoring intelligently. The ongoing development of the C++ STL ITS applies practices from Extreme Programming methodology and J2EE technologies
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