Implementation of Decision-Making Mechanism in the Intelligent Tutoring System Based on the Expert Systems Module

The article discusses the general principle of organizing an intelligent scheduler (solver) of an experimental intelligent tutoring system based on the mechanisms of expert systems and cognitive visualization. The FLM_Builder program module was used as the basis for implementing the scheduler. The specifics of the solver for the Python interpreter are described and the stages of forming expert system models are given. To illustrate the operation of the inference mechanism, the task of individualizing the composition of a training course with subsequent visualization in the notation of cognitive maps of knowledge diagnostics corresponding to the cross-cutting approach to the analysis of the educational situation in the tutoring system is considered.