Automatic Generation of Problem Scenarios for Assessment of Methodological Knowledge

The article explores the concept of knowledge and knowledge models concerning their application in evaluating the assimilation of methodological knowledge. It analyzes the benefits of employing test formats for assessment in the learning process and their influence on the enhancement of students’ critical thinking and analytical skills. The potential for automating the generation of test sets using computer technologies is investigated. A framework for formalizing problem scenarios based on ontology models is proposed, aiming to organize and generalize knowledge in this domain. A method for generating problem scenarios to assess methodological knowledge is developed, leveraging computer algorithms and artificial intelligence. This approach facilitates the creation of high-quality test sets with diverse tasks and scenarios, thereby enhancing the effectiveness of evaluating students’ knowledge. Through experimental research, a system of variable parameters is identified, enabling the customization of test sets to different student groups and educational contexts. The results obtained validate the efficacy of the proposed method and underscore its significance in enhancing the assessment and teaching of methodological knowledge in educational settings.