Effects of collaboration on students’ learning using Intelligent Tutoring System

Abstract

Computer-based learning tools called Intelligent Tutoring Systems (ITS) assist students to become better learners by simulating human tutors using Artificial Intelligence (AI) approaches. Students can interact using collaborative ITSs from various locations to study, discuss, and articulate concepts relevant to a certain problem. This paper presents a collaborative ITS to teach UML that is built to enable students to effectively communicate and share each other's mistakes. The ITS is capable of detecting and identifying student errors and offers students suggestions during the problem-solving stage, giving them guidance on how to proceed. The ITS also determines a student's current level of thinking and intellect in order to assign them activities that need more attention. The evaluations conducted for this study revealed that the experimental group had considerably more learning gains (81% scores on the posttest) than the control group, where students only showed a very low significant change in their learning with posttest scores of 46%