Implementing an intelligent tutoring system focused on addressing the learning preferences of students in Ashesi

Abstract

Education provision in developing African countries like Ghana is saddled with recurring roadblocks and problems, including insufficient resources to accommodate the high demand for education. This places an additional burden on faculty, impacting both them and the learner, who cannot get in-depth assistance to overcome challenges in their learning journey due to time constraints. This project focuses on creating an AI-powered Intelligent Tutoring System (ITS) to tackle such educational challenges by leveraging the great potential gains of personalized learning. Utilizing a Large Language Model (LLM), the system generates content tailored to each student's learning preference and knowledge level. Key features include personalized content generation based on two learning preferences deduced from requirements analysis, an AI chatbot for real-time support, and post-session assessments. In addition to exploring a novel approach to ITS implementation, this research looks to start a dialogue on the widespread use of these systems in a more official capacity as a possible augmentation to the educational space in Ghana and other developing African countries. By integrating personalized instruction and adaptive learning paths, the system aims to boost student comprehension and retention of course material. Testing and user feedback suggest that the proposed system holds some value among learners and offers a promising approach to personalized education, though there is room for improvement in user profiling and assessment diversity.