Intelligent Tutoring Systems (ITS) are computer-based systems that use artificial intelligence (AI) and machine learning techniques to provide personalized instruction and feedback to students. ITS are designed to adapt to each student's individual needs, learning style, and pace, and provide them with customized feedback and guidance.

The goal of ITS is to improve students' learning outcomes by providing them with high-quality, interactive instruction that is tailored to their needs. ITS can be used to teach a wide range of subjects, from basic arithmetic to complex engineering concepts, and can be used in a variety of settings, including classrooms, online learning platforms, and corporate training programs.

The core components of an ITS typically include a knowledge base, a student model, a problem-solving module, and an interface that allows students to interact with the system. The knowledge base contains the content that the ITS teaches, while the student model tracks the student's progress and identifies areas where the student may need additional support. The problem-solving module provides students with feedback and guidance as they work through problems, and the interface allows students to interact with the system and receive feedback.

Figure 1. Intelligent Tutoring Systems (ITS)

Figure 1 shows Intelligent Tutoring Systems (ITS). The use of AI and machine learning techniques in ITS allows them to adapt to each student's individual needs and provide personalized instruction and feedback. For example, an ITS may adjust the difficulty level of problems based on the student's performance, or provide additional support and guidance when the student is struggling with a particular concept.

One of the newly developed methods involves artificial intelligence allowing a teacher to teach a computer, which then, in turn, teaches a student. In other terms, a computer is being taught how to teach by a human teacher. [1]

In this method, a human teacher demonstrates to the computer how to solve specific problems like multicolumn addition. If the computer provides the wrong solution to the problem, the human teacher then corrects it. [1]

One of the breakthrough aspects of this research and method is that the computer system can solve problems within a topic by generalizing. This means that it does not just solve the problems that it was taught, but it can venture out on its own into new territory. [1]

Overall, Intelligent Tutoring Systems are a promising area of research that has the potential to transform the way we teach and learn. As the field continues to evolve, we can expect to see more advanced ITS that use even more sophisticated AI and machine learning techniques to provide even more personalized and effective instruction.

References:

1. https://medium.com/@roybirobot/how-intelligent-tutoring-systems-are-changing-education-d60327e54dfb

Cite this article:

Hana M (2023), Intelligent Tutoring Systems (ITS), AnaTechmaz, pp.223