One of the aspects of developing a universal task designer for training systems

The paper considers the issue of building a block hierarchy of software and information models that simulate the subject area in training systems, based on the principle from simple to complex, from elementary functions to more complex ones. This allows us to implement the principle of adaptability in training systems – the ability to manage the complexity of the training process depending on the competence of the trainee. An approach to the construction of a universal task constructor for training systems based on the representation of the training process in the form of changing a finite number of parameters of the training block by affecting it by the trainee is proposed. The training block in this setting is considered as a set of parameters of various types. A method for evaluating the training process is proposed, which involves checking the state of the block at the end of training, that is, checking whether the parameter values match the specified ones. It allows you to create flexible systems for evaluating knowledge. Correlation of certain parameters with the skills of the trainee allows automating the process of controlling the level of his subject competence and makes it possible to implement the principle of adaptability of training systems, which consists in a gradual increase in the complexity of the training process. A prototype of a universal task designer for training systems is presented. Its use significantly simplifies task editing, neglecting the use of programming environments.

1. Trembach V.M. Electronic training systems using intelligent technologies. Open education. 2013;(4):52-62.

2. Golenkov V.V., Emelyanov V. V., Tarasov V. B. Virtual departments and intellectual training systems. Artificial intelligence news. 2001;(4).

3. Rybina G.V. Expert systems and tools for their development: some results. Informationmeasuring and control systems. 2013;11(5):35-48.

4. Stefanyuk V.L. Behavior of a quasi-static shell in a changing fuzzy environment. National conference with international participation "Artificial intelligence 94": collection of scientific papers. 1994;(1):199-203

5. Tarasov V.B. From multi-agent systems to intellectual organizations: philosophy, psychology, Informatics. 2002.

6. Trembach V.M. Systems of management of bases of evolving knowledge for solving problems of continuous education: monografiya. 2013.

7. Telnov Y. The Model of Continuous Profession-oriented Learning in the E-environment Based on a Competence Approach and Academic Knowledge Management. 11thEuropean Conferences of Knowledge Management Systems. 2010, Porto

8. Guzik V.F., zolotovsky V. E., Pereverzev V. A. Training systems based on local computer networks. SFU news. Technical science. 2002;(2):175-179