A method for determination of an opening learning scenario in intelligent tutoring systems

Abstract

The intelligent tutoring systems should guarantee an effective learning. Students who use those systems should achieve better learning results in a shorter time. Our previous research pointed out that the personalization of the learning scenario allows to satisfy the mentioned postulates. In this paper the method for determination of an opening learning scenario is presented. Before a student begins to learn an opening scenario is determined based on information provided during a registration process. User is offered the optimal learning path suitable for his learning styles and a current knowledge level. Worked out method applied the ant colony optimization technique. The effectiveness of the proposed solution was tested in a specially implemented environment. The researches demonstrate that the algorithm gives quite good results, because 66% of the learning material in the determined learning scenario were adapted to student's learning styles. © 2013 Springer-Verlag.