Characteristics and Application of Intelligent Tutoring Systems: A Review

Recently, technology has developed rapidly, this has an effect on the integrated education system model with artificial intelligence techniques. Such educational models are known as Intelligent Tutoring Systems (ITSs). This paper aims to evaluate the characteristics of several ITS models that are applied to various fields of education. The original studies from 2009 to 2021 were extracted from the ACM Digitally Library, IEEEXplore, Scopus, Google Scholar, Science Direct, and Springer databases. From the search on the database, 26 papers were obtained which were used as the focus of evaluation based on the inclusion criteria as stated in the Kitchenham framework. From the results of the evaluation, the conclusion is that computer science is the largest field that applies ITS (50%). Meanwhile, artificial intelligence techniques are applied in ITS, the greatest frequency is NLP-based techniques (30.7%) and intelligent agent techniques (26.9%). These techniques are proven to be able to provide guidance and instructions according to user needs, evaluate processes learning for learners, defining new student models, and categorizing learners on ITS.