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An intelligent tutoring system is a computer system that aims to provide immediate and customized instruction or feedback to learners, usually without requiring intervention from a human teacher. ITSs have the common goal of enabling learning in a meaningful and effective manner by using a variety of computing technologies. There are many examples of ITSs being used in both formal education and professional settings in which they have demonstrated their capabilities and limitations. There is a close relationship between intelligent tutoring, cognitive learning theories and design; and there is ongoing research to improve the effectiveness of ITS. An ITS typically aims to replicate the demonstrated benefits of one-to-one, personalized tutoring, in contexts where students would otherwise have access to one-to-many instruction from a single teacher (e.g., classroom lectures), or no teacher at all (e.g., online homework). ITSs are often designed with the goal of providing access to high quality education to each and every student.
Already used by hundreds of thousands of students, automated tutoring products driven by artificial intelligence (AI) are poised to become a significant presence in classrooms within the next decade, forever changing the way learning is done.
Key to that proliferation is AI tutoring’s ability to personalize education. Essentially, with an AI tutor at their side, a student has an incredibly smart digital friend with unlimited patience and 24/7 availability, skillfully programmed to sense the best way to impart knowledge to that particular student.
“The advantage of an AI system is that it can give 100% attention to each student, and that it can tailor material to an individual student’s abilities and needs,” says Kevin Leyton-Brown, a computer science professor at the University of British Columbia.
The companies providing AI tutors have found their greatest success in targetting highly specific, well-defined disciplines in which the answers students seek are clearly right or wrong.