Operator-Navigator Activity Diagnostics System based on Task Approach
Introduction: Computerization of educational process and the use of remote adaptive learning systems provide opportunities for inclusive continuous training of highly qualified personnel capable of solving a wide range of applied engineering tasks. Monitoring their knowledge and skills presumes continuous diagnostics of the learners. Purpose: Developing a navigational skill diagnostic system based on a task approach with binary-tree output and graphosemantic ranking of individual actions by their complexity when a learner is solving a typical practical problem. Results: We have formulated the major task solved by an expert diagnostic system during the training of aviation specialists, which is the diagnostics of their knowledge and practical skills. The graphosemantic approach allowed us to objectively rank individual actions of an operator when constructing a private semantic graph for the problem being solved by a learner. When creating and operating the remote adaptive learning system, binary trees allowed us to analyze all possible solutions to the problem and program the best solution on the basis of simple mathematical operations. Application of the above approaches with the help of fuzzy logic allowed us to propose a hypothesis about the possibility to calculate the degree of approximation between the learner’s answer and the standard (correct) answer, thereby effectively evaluating his/her knowledge and skills at all stages of solving the problem. Practical relevance: The developed system provides the opportunity to reduce training time, intensify the learning process and increase the degree of mastering knowledge and skills. The load on the instructors and teachers decreases as they become free from a number of technological operations related to the processing and verification of the test results.