Multi Path Based Intelligent Tutoring System

Abstract

– The paper introduces a system that has several paths to solution in an intelligent tutoring system platform and then chooses the most desired path to the solution. The desired path in this case is the right path to knowledge or solution that the student tends to understand after several attempt. This system models the student's level of assimilation while tutoring with any chosen path per time. It possesses the capability to note or store the best path to solution at any given time so as to use the best path to solution whenever it has to deliver lecture the next time thereby not start all over again. This ensures that tutoring is done using the desired and best path to knowledge, thereby reducing the student learning curve. This system still works with the previous intelligent system structures as discussed by Nwana, 1990;[11] , Freedman, 2000;[2] , and Nkambou et al, 2010;[3] but rather than just have the knowledge base populated with just one path to solution within the domain model, it will now contain more than one path to solution, then after several teachings and modeling the students based on their understanding level in each case, the system should be able to know the best path which is the shortest and desired path to the solution. In this work, we shall be looking at how this system works and its relevance to our tertiary institutions in Nigeria.