Utilizing Optimization Technique as A Decision Making Tool for Modeling Student Comprehension Ability in an Its

Abstract

This paper is focused on the utilization of optimization techniques in finding the solution to the appropriate learning style suitable for each student in an Intelligent Tutoring System, (ITS). The quest for this solution in an ITS, was borne out of the need to address the problems associated with learning systems. This major problem concerns the ability to determine the comprehension level of a student being taught before he proceeds to take an examination. Interestingly, there are several researches conducted in the past using several techniques in finding answers to the problems as reported in recent literatures, however, the researchers had not recorded maximum success. Therefore in our paper, we intend to find solution to the best learning style among many that is suitable for each learning student and to perpetually assign it to that student for subsequent learning. This option is chosen because the major problem students face while learning in a particular domain is that of not being able to comprehend or have a grasp on what is taught. In our approach, we are not focusing on the content which is an integral part of the knowledge base of the system but the path with which the tutor agent of the system uses to pass the content in the domain expert of the system down to the student module of the system. We deploy four learning paths which is the learning styles such as Auditory Learners (Through Hearing), Visual Learners (Through seeing), Kinesthetic Learners (Through Touch or practice) and hybrid (Combination of two or more) were used while modeling the student. Optimization technique was then deployed to find out the appropriate learning style suitable for each student. Therefore in this paper, we entirely x-rayed the concept of utilizing optimization technique as a decision making tool in modelling student in a typical learning environment.