UDC: 
372.8
SAMYLKINA NADEZHDA Nikolaevna
Доктор педагогических наук, Professor of the Department of Theory and Methodology of Informatics Education, Institute of Mathematics and Informatics, Moscow Pedagogical State University, nsamylkina@yandex.ru, Moscow
Kalinin Ilya A.
Кандидат педагогических наук, Cand. Sci. (Pedag.), Assoc. Prof., Head of Informatization Administration, Department of Digital Development, Moscow State Linguistic University, Associate Professor, Department of International Information Security, Institute of Information Sciences, kalininIlya@mail.ru, Moscow

Preparation of Schoolchildren for the Olympiad on Artificial Intelligence

Abstract: 
The article presents a small part of the research results devoted to the development of scientific and methodological support of variant teaching of the basics of artificial intelligence in the course of computer science of basic general and secondary general education, concerning the preparation of schoolchildren for the Olympiad on artificial intelligence. The aim of the article is to actualize the problem of developing or selecting the necessary task material for purposeful preparation for school Olympiads on artificial intelligence. The content of theoretical and practical modules of the basics of artificial intelligence developed as a result of the research includes olympiad training in artificial intelligence for basic and high school students studying computer science at an advanced level. The research methodology consists of: integrative approach to the development of the methodology of variant teaching of the basics of artificial intelligence and the implementation of possible educational trajectories in the basic educational programs of basic general and secondary general education; experience in the development of the concept and content of the first All-Russian Olympiad of schoolchildren of grades 8-11 on artificial intelligence; expert activity in the Russian Union of Schoolchildren’s Olympiads and the results of surveys of teachers. General theoretical and empirical research methods were used. The conclusion about possible solution of the problem of development of training tasks for purposeful preparation of schoolchildren for the Olympiad on artificial intelligence and realization of the course on choice of participants of educational relations with the use of standard tasks of three stages of the Olympiad on artificial intelligence is made in the conclusion.
Keywords: 
artificial intelligence; AI Olympiad; variable AI training; computer science; Python programming; elective course; advanced level; learning trajectories; training tasks; stages of the Olympiad
References: 

1. Grigoriev, S. G., Kalinin, I. A., Samylkina, N. N., 2022. System of tasks for the first All-Russian Olympiad of schoolchildren on artificial intelligence. Informatics and Education, no. 37 (3), pp. 12–20. DOI: 10.32517/0234-0453-2022-37-3-12-20 (In Russ.)
2. Ryzhova, N. I., Trubina, I. I., Koroleva, N. Y., Filimonova, E. V., 2022. Artificial intelligence as an actual trend of the content of informatics teaching in conditions of digitalization. Teachers XXI century, no. 2–1, pp. 11–22. EDN: ZGIENM. DOI: 10.31862/2073-9613-2022-2-11-22. (In Russ.)
3. Yang, D., Shi, B., Samylkin, A., 2022. Graphical Neural Networks for the Global Economy with Microsoft DeepGraph. WSDM 22: Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining. NY, Association for Computing Machinery, 1655. DOI: https://doi.org/10.1145/3488560.3510020 (In Eng.)
4. Machalica, M., Samylkin, A., Port, M., Chandra, S., 2019. Predictive Test Selection. 2019 IEEE/ACM 41st International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP), pp. 91–100. DOI: https://doi.org/10.1109/ICSE-SEIP.2019.00018 (In Eng.)
5. Russell, S., Norvig, P., 2007. Artificial intelligence: a modern approach, 2nd ed. Moscow: Williams; 1408 p. (In Russ.)
6. Broussard, M., 2020. Artificial Intelligence: The Limits of Possible. Moscow: Alpina non-fiction Publ., 362 p. (In Russ.)
7. Giarratano, D., Riley, G., 2007. Expert systems: principles of development and programming: 4th ed. Moscow: Williams Publ., 1152 p. (In Russ.)
8. Kalinin, I. A., Samylkina, N. N., 2013. Informatics. Advanced level. 11th grade. Moscow: BINOM. Laboratory of Knowledge, 216 p. (In Russ.)
9. Yasnitsky, L. N., 2008. Introduction to artificial intelligence. Moscow: Academy Publ., 176 p. (In Russ.)
10. Yasnitsky, L. N., 2012. Artificial Intelligence. Elective course: textbook. Moscow: BINOM. Laboratory of Knowledge, 197 p. (In Russ.)
11. Samylkina, N. N., Salakhova, A. A., 2022. Teaching the basics of artificial intelligence and data analysis in the course of computer science at the level of secondary general education: monograph. Moscow: MPSU Publ., 228 p. DOI:
https://doi.org/10.31862/9785426310643 (In Russ.)
12. Stoyanov, S., Glushkova,T., Papancheva, R., 2021. Source intellect. Knowledge representation through logic. Bourgas, Logic Programming LLC Art Publishing House, 248 p. (In Russ.)
13. Joshi, P., 2019. Artificial intelligence with examples in Python. St. Petersburg: Dialectics Publ., 448 p. (In Russ.)
14. Levchenko, I. V., 2019. Main approaches to teaching elements of artificial intelligence in the school course of informatics. Informatics and Education, no. 34 (6), pp. 7–15. DOI: https:// doi.org/10.32517/0234-0453-2019-34-6-7-15 (In Russ.)
15. Bogdanova, A. N., 2021. Elective course “Fundamentals of artificial intelligence” for high school students. Informatics at school, no. 20 (7), pp. 27–33. DOI: https://doi.org/10.32517/2221-1993-2021-20-7-27-33 (In Russ.)
16. Stoyanov, S., Glushkova, T., Papancheva, R., 2019. Artificial Intelligence. Problem solving through search. Bourgas, Logic Programming LLC Art Publishing House, 312 p. (In Eng.)
17. Agrawal, R., Srikant, R. Fast algorithms for mining association rules in large databases. Proc. of the 20th Int. Conf. on Very Large Data Bases (VLDB). Santiago, Chile, 1994, 487–499. Available at: https://vldb.org/conf/1994/ P487.PDF(In Eng.)
18. Pickover, K., 2021. Artificial Intelligence. An illustrated history. From automata to neural networks. Moscow: Sindbad Publ., 250 p. (In Russ.)
19. Friedl, J., 2008. Regular expressions. St. Petersburg: SymbolPlus Publ., 608 p. (In Russ.)
20. Variative teaching of the basics of artificial intelligence in general education on the basis of integrative approach: a monograph / S. D. Karakozov, N. N. Samylkina, A. A. Salakhova, E. A. Samokhvalova. Moscow: MPSU, 2024, 360 p. (In Russ.)