INTELLIGENT TUTORING SYSTEMS AND ADAPTATION OF TEACHING TO USER LEARNING PROFILES

In the 21st century, the demand for teaching and learning mediated by digital technology, especially suited to learning profiles, has grown. Thus, considering the need to discuss the adaptability capacity of Intelligent Tutoring Systems (ITS), this text aims to understand how these systems perform the adaptability of content and activities to different user learning profiles. To achieve this, an essay was used, derived from part of the theoretical framework of a bibliographic research, carried out from the databases of the free journals portal of the Coordination for the Improvement of Higher Education Personnel (CAPES), of the journals Scientific Electronic Library Online (SCIELO) and Google Scholar. As a result, it was observed that Computer-Assisted Instruction is carried out from instructional activities, generally structured in questions and answers. On the other hand, microworld systems advanced in the proposition of cognitive abilities and reflective thinking. While generative systems are able to produce instructional material automatically, despite solving problems in a way very different from what people use to solve them. Whereas Computer-Assisted Intelligent Instruction systems are able to offer the user an intelligent tutoring. Finally, the concept of personalized education and its founding principles, proposed by Hoz (1988), are presented as a theoretical framework that can contribute to the work of ITS developers seeking to expand the capacity of these computer systems to adapt teaching to the learning profile of each user.