AUTOMATIC TRAINING EXPERT SYSTEM

Abstract

Group training in general secondary education, secondary and higher specialized educational institutions involves the transfer of knowledge and the development of skills, with an orientation to the "average" according to the abilities of the student. At the same time, achieving such a level of training as "skills" is, in principle, impossible. The level of skills requires, as a rule, individual training with the use of various kinds of teaching and training systems together with the method of iterative learning. The coronavirus pandemic (COVID-19) and the transition to distance learning have intensified the development of information and communication technologies (ICT) for teaching without the presence of a teacher. All this determines the relevance of the development of an automatic training system based on an expert system that ensures, in the absence of a teacher, the achievement of the maximum for each student, depending on his intelligence, the required level of training. In this paper, the structure of an automatic learning system is proposed, which ensures the assimilation of educational material to a given level of learning without the participation of a teacher. Using the example of using such a system for training operators of an arc steelmaking furnace, the work of the system elements is shown: the object simulator model, the trainee error analysis blocks, the synthesis of training information, as well as database and knowledge functions. The issues of obtaining andformalizing the knowledge of expert teachers are considered separately. Examples of the formation of knowledge frames for the training of chipboard steelworkers are given. For example, to teach the process of mixing an electric steelmaking process, 81 frames of information are needed, providing educational comments for all kinds of mistakes of the trainees. Conclusions were drawn based on the results of the work.