The effects of generative artificial intelligence on intelligent tutoring systems in higher education: A systematic review

Abstract

There is a lack of research regarding artificial intelligence (AI) applications in education settings, especially on whether generative AI can effectively advance intelligent tutoring and begin a new era of AI-powered effective tutors. The purpose of this systematic review was to thoroughly explore the evolution, potential applications, and challenges associated with AI-powered tutoring systems, formerly known as intelligent tutoring systems (ITSs), within science, technology, engineering, and mathematics (STEM) disciplines in higher education. The research identified five prominent themes regarding the evolution of ITSs in the last five years: 1) integration of AI; 2) personalized and adaptive learning; 3) learning analytics; 4) inclusion and equity; and 5) STEM disciplines. In particular, it was found that ITSs are one of the key applications of AI technologies in education. The studies reviewed indicate that emerging technologies, including virtual reality, augmented reality, robots/avatars, and voice assistants, will likely play crucial roles in the next generation of these systems. Additionally, emphasis was placed on online and remote learning, gamification, inclusion, and equity.

In contrast, ethical issues are becoming a significant concern due to the enormous data usage of AI, specifically personal and other sensitive information. There is a general distrust toward AI technology, and ITSs are still new to many educators. Therefore, the systematic review evaluates how crucial it is to harness the potential of generative AI and ITSs responsibly. As we move forward, ensuring that ITSs complement, rather than replace, the essential role of human tutors is critical.

Keywords: intelligent tutoring systems; generative artificial intelligence; higher education; STEM disciplines