V. V. Borisov, S. P. Yanukovich, T. V. Mrochek, M. V. Vorob'ev, A. Yu. Mirankov Intelligent Management of Preparation for the Olympiads in Programming Based on Swarm Intelligence Algorithms
Existing approaches to managing the processes of preparation for contests in programming are usually not focused on intelligent interactive support for learning management, and the software tools based on them do not allow to effectively process and provide information to learners to form in-dividual and team trajectories for preparing for programming contests. In addition, there is no accounting for personal and psychological qualities of learners that reduces the effectiveness of preparation for individual and team contests. The proposed approach to the organization of intelligent management of preparation for the Olympiads in programming is based on a systemic approach, on the theory of organizational systems management and implementation of the whole cycle of automated management of IT specialists training (including the stages of planning, organization, control and motivation). It is proposed to adaptively form educational trajectories on the basis of swarm intelligence algorithms modified taking into account the peculiarities of managing preparation for Olympiad programming. For participants of individual Olympiads, it is proposed to form individual educational trajectories based on the modified Firefly algorithm. For participants of team Olympiads, it is proposed to form team educational trajectories based on a modified Fish School Search algorithm. It is proposed to sup-plement the training process with recommendations and workouts selected based on the results of psychological testing and aimed at developing personal and psychological qualities of the learners. The recommendations performed throughout the preparation process until the threshold values of personal and psychological qualities necessary for participation in Olympiads are reached.
Keywords: Olympiad programming, contest, swarm intelligence algorithms, modified Firefly and Fish School Search algorithms, online judge systems, individual and team educational trajectories.
1. Pavlova, O., and E. Yanova. 2017. Olympiads in Informatics as a Mechanism of Training World-Class Professionals in ICT. Olympiads in Informatics. 11:109–121.
2. Chiriac, L., and L. Mihălache. 2019. The methodology for preparing undergraduate students for olympiads in informatics in extended format. Acta et Commentationes, Sciences of Education. 4(18):37–45.
3. Dolinsky, M. 2017. A New Generation Distance Learning System for Programming and Olympiads in Informatics. Olympiads in Informatics. 11:29–39.
4. Wang, G. P., S. Y. Chen, X. Yang, and R. Feng. 2016. OJPOT: Online judge and practice oriented teaching idea in programming courses. European Journal of Engineering Education. 41:304–319.
5. Gorchakov, L. V., A. N. Stas', and D. V. Kartashov. 2017. Obuchenie programmirovaniyu s ispol'zovaniem sistemy ejudge [Programming training using the ejudge system]. Tomsk state pedagogical university bulletin. 9(186):109–112.
6. Francisco, R. E., and A. P. Ambrosio. 2015. Mining an Online Judge System to Support Introductory Computer Programming Teaching. Available at: http://ceur-ws.org/Vol-1446/smlir_submission1.pdf (accessed: 15.08.2020).
7. Xu, B., S. Yan, X. Jiang, and F. Shaoge. 2020. SCFH: A Student Analysis Model to Identify Students’ Programming Levels in Online Judge Systems. Symmetry. 12(4):601–611.
8. Toledo R. Y., Y. C. Mota, and L. Martínez. 2018. A Recommender System for Programming Online Judges Using Fuzzy Information Modeling. Informatics. 5:17–33.
9. Verdú, E., L. M. Regueras, M. J. Verdú, J. P. Leal, J. P. de Castro, and R. Queirós. 2012. A distributed system for learning programming on-line. Computers and Education. 58(1):1–10.
10. Verdú, E., M. J. Verdú, L. M. Regueras, J. P. de Castro, and R. García. 2012. A genetic fuzzy expert system for automatic question classification in a competitive learning environment. Expert Syst. Appl. 39:7471–7478.
11. Yu, X., and W. Chen. Research on three-layer collabora-tive filtering recommendation for online judge. 2016. Proc. of the 2016 Seventh International Green and Sustainable Computing Conference (IGSC), Hangzhou, China. 1–4.
12. Caro-Martinez, M., and G. Jimenez-Diaz. 2017. Similar Users or Similar Items? Comparing Similarity-Based Ap-proaches for Recommender Systems in Online Judges. International Conference on Case-Based Reasoning. Springer, Cham. 92–107.
13. Watanobe, Yu., Ch. Intisar, R. Cortez, and A. Vazhenin. 2020. Next-Generation Programming Learning Platform: Architecture and Challenges. SHS Web Conference 77:01004.
14. Saito, T., and Yu. Watanobe. 2020. Learning Path Recommendation System for Programming Education Based on Neural Networks. International Journal of Distance Education Technologies (IJDET). 18(1):36–64.
15. Lalitha, T. B., and P. S. Sreeja. 2020. Personalised Self-Directed Learning Recommendation System. Procedia Computer Science, Elsevier. 171:583–592.
16. Nikitina, L. N., A. N. Shikov, A. Bakanova, K. V. Loginov, S. A. Okulov, and A. V. Chunaev. 2018. The Concept of Personalized Corporate E-training and Development Based on Competencies and Individual Preferences of Employees. Journal of Creative Economy. Vol. 12. 7:995–1004.
17. Korabel'shchikova, S. Yu., E. A. Tolkacheva, and K. P. Butin. 2019. O sisteme podgotovki komandy k olimpiadam po programmirovaniyu [About the System of Team Training to the Programming Olympiads] // In proc.: Sovremennye informatsionnye tekhnologii i IT-obrazovanie. Proc. of 3rd Intern. Sci. Conf. “Convergent cognitive information technologies» and XIII Intern. Sci. and Pract. Conf. “Modern information technologies and IT education”. Lomonosov Moscow State University; Federal research center “Informatics and management” of the Russian Academy of Sciences. 164–173.
18. Menai, M., H. Alhunitah, and H. Al-Salman. 2018. Swarm intelligence to solve the curriculum sequencing problem. Computer Applications in Engineering Education. 26(5):1393–1404.
19. Yanukovich, S. P., T. V. Mrochek, and D. S. Orekhovsky. 2018. Cikl avtomatizirovannogo informacionnogo upravlenija podgotovkoj IT-specialistov [A cycle of automated information management of training IT-specialists]. Proc. 8th International Conference Energy, Computer Science, Innovation. Smolensk. Vol. 3. 53–57.
20. Borisov, V. V., S. P. Yanukovich, T. V. Mrochek, and D. S. Orekhovsky. 2020. Software complex SkillsForYou for the IT specialists training management. Software and Systems. Vol. 33. 2:177–185.
21. Novikov, D. A. 2009. Teoriya upravleniya obrazovatel'nymi sistemami [The Theory of Management of Educational Sys-tems]. Moscow: Narodnoe obrazovanie, 416 p.
22. Novikov, D. A. 2009. Struktura teorii upravlenija social'no-jekonomicheskimi sistemami [The structure of the theory of management of socio-economic systems]. Large System Management. 24:216–237.
23. Yanukovich, S. Р. 2020. Method of managing the process of teaching olympiad programming based on algorithms of swarm intelligence. Innovatsii [Innovations]. 1(255):94–102.
24. Bobryakov, A. V., S. P. Yanukovich, K. V. Zakharchenkov, and V. V. Borisov. 2020. A Method for Managing Engineers Training Processes using Swarm In-telligence Algorithms, 2020 V International Conference on Information Technologies in Engineering Education (Inforino). Moscow. 1–5.25. Yang, X.-Sh. 2010. Firefly Algorithm, Stochastic Test Functions and Design Optimisation. International Journal of Bio-Inspired Computation. Vol. 2. 2:78–84.
26. Bastos-Filho C., F. Lima Neto, A. Lins, A. Nascimento, and M. Lima. 2008. A novel search algorithm based on fish school behavior. IEEE International Conference on Systems, Man and Cybernetics. Singapore. 2646–2651.
27. Karpenko, A. P. 2017. Modern Search Engine Optimization Algorithms. Nature-Inspired Algorithms. 2nd edn. Moscow: Izd-vo MGTU im. N. E. Baumana. 446 p.
28. Fetiskin, N. P., V. V. Kozlov, and G. M. Manuilov. 2002. Sotsial'no-psikhologicheskaya diagnostika razvitiya lichnosti i malykh grupp [Social and Psychological Diag-nostics of Personality Development and Small Groups]. Moscow: Izd-vo instituta psychoterapii. 339 p.
29. Bloom, B. S. (Ed.). 1956. Taxonomy of educational objectives: The classification of educational goals. Handbook I: Cognitive Domain New York: McKay.
30. Yanukovich, S. P., K. V. Zakharchenkov, V. P. Shut', T. E. Titov, N. S. Musabirova, and O. O. Bykova. Pro-gram for evaluating the personal characteristics and psychological qualities of IT specialists. Certificate of state registration of computer programs no. 2019661028. Application no. 2019660005, date of receipt 08.08.2019, registration date 16.08.2019.
31. Yanukovich, S. P., K. V. Zaharchenkov, M. V. Vorob'ev, A. Ju. Mirankov, and Ju. V. Uzjanova. Program for teach-ing olympiad programming based on swarm intelligence algorithms. Certificate of state registration of computer programs no. 2020612506. Application no. 2020611565, date of receipt 17.02.2020, registration date 25.02.2020.