Intelligent Tutoring System Design Using Markov Decision Process

Class learning is a teaching and activity involving both teachers students. Students in the class have different levels of intelligence, divided into three categories: lowest, average, most intelligent. Teachers usually pay less attention to intelligent Consider student who not enough remain school. However, if smart required repeat content he already comprehends, will become bored. Therefore, this study developed an tutoring system (ITS)-based application with Markov decision process (MDP). The combination ITS MDP enabled intelligence determine appropriate subsequent step by delivering tutorials examination questions that guide students efficiently attain levels.