Intelligent Tutor Recommender System for On-Line Educational Environments

This paper presents a method of using a classification procedure for retrieval of the most appropriate tutors in online educational environments. The main goal is assisting learners to find the most suitable colleagues that can provide them help. The retrieval is based on a user model built from experiences of previous generations of students. Performed activities represent the raw input data(i.e., the experiences), that one obtained from on-line educational environment. The goal of the developed system is to provide a list of colleagues that are willing and able to provide help. The student that is looking for a tutor will be aware of his weakness, his place among his colleagues and get some intuition regarding needed future activities that may improve effectively his knowledge level. The data processing for the retrieval mechanism is based on a classical classification engine that is custom designed for fulfilling the presented goal.