employee
employee
Testing technology is the most important in the educational process, medicine, diagnostics of the quality of products and in many other areas. This technology is especially relevant in connection with the introduction of digital technologies and artificial intelligence systems. In this article, a new mathematical model of the organization of the student testing procedure has been developed. The apparatus of the theory of random processes is used to analyze the methods of dispatching the testing procedure. A method is shown for determining an important indicator of the organization of the testing procedure, the rate of change in the number of assignments received by a student in a given time. The characteristics of this indicator as a random process are calculated: mathematical expectation, variance and correlation function. It is shown that the rate of change in the number of tasks for their simplest flow is a stationary white noise (the number of tasks at different time points is not correlated). In this case, the testing process is stationary, i.e. the statistical characteristics of the random process do not change over time. The model developed in the article can be used not only in the educational process, but also for diagnosing product quality, in medicine, when testing software and other areas.
learning process, random function, flow of test tasks, knowledge verification, diagnostics
1. Ganicheva A.V., Ganichev A.V. Matematicheskaya model' ocenki kachestva testirovaniya // Informatizaciya obrazovaniya i nauki, 2020. № 4 (48). – S. 114-123.
2. Pechenyy E.A., Nuriev N.K., Ali A.A. Matematicheskaya model' effektivnogo administrirovaniya mnogokanal'noy SMO v sisteme kontrolya kachestva uchebnogo processa // Fundamental'nye issledovaniya, 2016. № 10-3. – S. 532-536.
3. Huziahmetova A.R., Nuriev N.K., Huziahmetova R.N. Ocenka prodolzhitel'nosti testirovaniya v zavisimosti ot slozhnosti testa // Sovremennye problemy nauki i obrazovaniya, 2019. № 3. S. 28.
4. Zaozerskaya L.A., Plankova V.A. Development of knowledge testing systems based on discrete optimization models // Journal of Physics: Conference Series. XIII International Scientific and Technical Conference «Applied Mechanics and Systems Dynamics», 2020. – S. 012183.
5. Ganicheva A.V. Testovye tehnologii v obuchenii: monografiya / A.V. Ganicheva i [dr.]. – Tver' Izdatel'stvo Tverskoy GSHA, 2011. – 130 s.
6. Yarmonov A.S., Vereschagina E.A., Frolov A.V. Testirovanie programm i matematicheskaya model' poiska oshibok v programmnom komplekse // Promyshlennye ASU i kontrollery, 2024. № 2. S. 42-44.
7. Ganicheva A.V. Teoriya veroyatnostey. – SPb: Lan', 2017. – 144 s.
8. Ventcel' E.S., L.A. Ovcharov. Zadachi i uprazhneniya po teorii veroyatnostey: ucheb. posobie dlya stud. vtuzov. M.: Izdatel'skiy centr «Akademiya», 2003. 448 s.
9. Golovin D.A. Matematicheskie modeli i algoritmy adaptivnogo testirovaniya na baze neyronnyh setey // Sovremennaya nauka: aktual'nye problemy teorii i praktiki. Seriya: Estestvennye i tehnicheskie nauki, 2024. № 10. S. – 104-108.
