On Solution Space of Intelligent Tutoring Systems for Programming: A Review

In intelligent tutoring systems (ITSs) for programming, a single programming exercise may produce many alternative solutions from students. It is difficult to build ITSs for programming due to the complexity and variety of possible solutions. In order for the students to learn from the system, it is necessary for them to receive feedback on their solutions to the programming exercises. To provide personalized feedback to students who are solving programming exercises effectively, the ITSs for programming must be able to cover a large space of possible solutions. The goal of this paper is to provide a brief review of the works in the literature related this problem.