DECOMPOSITION OF THE ACTIVITY OF THE AIR TRAFFIC CONTROL MANAGER IN THE ADAPTIVE TRAINING SYSTEM

Abstract

The use of adaptive learning systems is a direction for improving the training activities of air traffic control controllers, in particular on simulators. It is proved that adaptive learning, which includes artificial intelligence and flexible mechanisms for the formation of individually-adapted exercises, increases the effectiveness of learning compared with traditional training. In addition, the use of adaptive learning can save on the cost of training air traffic controllers by reducing the time spent without reducing its effectiveness. The process of adaptation consists of three phases: extracting user information, processing information for initialization, and updating the user model and using the user model for adaptation. One of the main problems of existing research in the field of intellectual educational systems is that they do not fully investigate the issue of the formation of individual strategies for air traffic controllers at the level of models and algorithms to provide effective feedback throughout all stages of their professional training. In the existing aeronautical training systems, the task of correction of educational activity is not realized. In the article the possibilities of forming an adaptive character and direction of study in the form of individual strategies of activity are examined with the help of structured set of study modes, typical errors according to the relevant criteria of evaluation and individual actions. Further research directions can be considered determination of weight coefficients of the importance of each error according to the relevant criterion of evaluation and weighting factors of the complexity of individual actions. Development of mechanisms for observing and analyzing the set of errors and their causes.