Multi Software Agent Based Intelligent Tutoring System

Achi Ifeanyi Isaiah, Agwu Chukwuemeka Odi · International Journal of Engineering Trends and Technology · 2015

This system deploys the multi agent approach which is one the Artificial Intelligence (AI) techniques of problem solving via software agent in carrying out training, teaching as close as human could handle it. Human beings could tell when a student is following a lecture or not by looking at the disposition of the students or their immediate reaction while the lecture is going on. The multi agent is deployed whenever the problem at hand is complex. The complexity here is being able to teach, and monitor the level of assimilation of the student concerned at the same time to be able to choose the right learning path while tutoring. This became pertinent at this time because of the mass failure during examination especially in Nigeria. Greater percentage of students fails examination because of lack of understanding of the subject matter. The only way the previous systems where able to know the level of assimilation of students under tutor is by conducting examination. It widely believed that if a student passes examination then he or she understood the subject matter and in the case of failure the opposite is the case. However, this is not always true. Recall that examination is not the true test of knowledge. Failure could be caused by many factors and one major factor which this system handles is proper assimilation while learning. Therefore, this system serves as a solution to the problem of mass failure in examination by ensuring that students grasp the subject matter on learning before facing examination. In this paper, we x-rayed the architecture of a typical Intelligent Tutoring System (ITS) which is formed by the three components that generally characterize an ITS - the Student Model, the Domain Model, and the Pedagogical Model with special emphasis on the software agent that monitors students progress within the Pedagogical model and lastly draw conclusions.

Read the paper · More papers on PaperTik