Cognitive Modeling of Information Support for Game-Based Automated Learning

Purpose of research. The main goal of this work is to increase the efficiency of automated game learning based on cognitive modeling. Based on the methodology of system analysis and cognitive modeling of weakly structured situations, the structure of a gaming automated training complex is proposed, which can be used in training personnel in various subject areas. In our case, staff training was simulated in stereotypical and non-stereotypical situations.

Methods. This work is based on the general provisions of systems theory and system analysis, mathematical graph theory (which is based on cognitive modeling). The main tool of cognitive modeling was the construction of fuzzy cognitive maps of Silov. A modification of the algorithm for calculating the main system indicators of a fuzzy cognitive map was proposed. Game modeling, based on business games, was used for automated learning. The concept of an operational game was introduced, then modeling of the development of some unfavorable situation was carried out using fuzzy cognitive maps..

Results. he main result of this work is the method of cognitive modeling of information support for game-based automated learning. Based on the developed methodology, a game simulation simulation of the operational game "House Fire" was carried out, which was based on the construction of a fuzzy cognitive map, for which the main quantitative system indicators of mutual influence, consonance and dissonance were calculated.

Conclusion: the developed methodology allows for game modeling of unfavorable (including emergency) situations, which in the future will ensure adequate behavior of students in real situations.

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