A method for developing intelligent simulators based on ontology of the subject domain

In academic disciplines, students are required to learn many new concepts, which necessitates extensive training with feedback. An intelligent simulator enables students to practice solving simple problems while receiving explanations for their mistakes, allowing teachers to focus on addressing more complex issues during lessons. This paper presents a method for developing intelligent simulators based on the ontology of the subject domain, implemented as web applications suitable for both classroom and extracurricular use. Representing the problem and the subject area model in RDF format enables logical inference using the Apache Jena Reasoner inference engine. An example is provided of an intelligent simulator designed for learning the order of operations in expressions, supporting the C++, C#, and Python programming languages. The simulator can explain errors, generate explanatory hints, and engage in educational dialogue through guiding questions. The simulator was tested with undergraduate and graduate students of the Faculty of Electronics and Computer Engineering at Volgograd State Technical University. Most students found the simulator to be more useful than traditional training tests. It can be employed both for independent study and as part of the educational process in classroom settings.