A framework of Intelligent Tutorial System to incorporate adaptive learning and assess the relative performance of adaptive learning system over general classroom learning

This paper presents a framework of intelligent tutorial system to incorporate adaptive learning and assess the relative performance of adaptive learning system over general classroom learning. In conventional classroom teaching and in distance learning the students may be from different backgrounds, their need of study and goal may be different; above all their ability to learn may not be similar. So teaching style and fitting teaching material may differ from student to student. A layered architecture of an Intelligent Tutorial System [ITS] for adaptive learning is proposed that assess the requirement, goal and capability of a student and dynamically sets a path for study, the instruction materials are dynamically selected as per the student’s level of understanding from a given set of instruction materials. The system monitors the student and changes the path of study automatically as per the performance. Formative and summative test are taken by the system for decision making – as to which material is best for student and for assessing student’s understanding level. The system also intelligently helps the user to overcome the misconceptions, as human teacher. Experimental results show the impressive improvement of the performances of students in distance mode learning using ITS following the proposed framework.