COGNITIVE COMPUTING AND INTELLIGENT TUTORING SYSTEMS IN EDUCATION TECHNOLOGY

Abstract

The rapid integration of cognitive computing and intelligent tutoring systems (ITS) into education technology has transformed traditional pedagogical methods, offering personalized, data-driven learning experiences. Cognitive computing models, inspired by human cognition, enhance the adaptability of ITS, enabling real-time analysis of students' learning patterns and providing tailored feedback to improve academic outcomes. This paper explores the potential of cognitive computing in optimizing intelligent tutoring systems by presenting various technological advancements, frameworks, and challenges associated with their implementation in educational settings. Through the examination of case studies, we identify how cognitive computing has shaped the design of ITS for K-12, higher education, and vocational training. We also discuss future directions for enhancing ITS with cognitive computing, particularly focusing on artificial intelligence, machine learning, and natural language processing techniques. The paper highlights how these advancements are poised to foster self-directed learning, increase engagement, and address diverse learner needs in a variety of educational contexts.