Algorithm for teaching basic strikes in WTF taekwondo

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PhD, Associate Professor G.I. Semenova1
PhD, Associate Professor I.V. Erkomaishvili1
Postgraduate student G.A. Ryabov1
Master student K.K. Pshenitsyn1
1Ural Federal University named after the First President of Russia B.N. Yeltsin, Yekaterinburg

Objective of the study was to identify the attitude of trainers to the algorithmization of the process of teaching the technique of basic strikes in WTF taekwondo.
Methods and structure of the study. The survey was conducted with the involvement of taekwondo coaches. The survey included closed and open questions aimed at identifying the coaches' experience in using the algorithmic approach, its perception and assessment of its effectiveness. 22 coaches participated in the survey.
Results and conclusions. A high percentage of the algorithmic approach used by taekwondo coaches has been revealed, which confirms its possible effectiveness in teaching basic strikes and improving athletic performance. The main problems of implementing the algorithmic method in training remain: lack of time, insufficient methodological materials and athletes' motivation, which requires additional research aimed at improving the quality of athletes' training. The article will be useful for coaches-teachers, instructors and all those interested in improving teaching methods in WTF taekwondo.

Keywords: algorithmization, training, basic strokes, taekwondo WTF.

References

  1. Rapoport, L. A. (1987). Algoritmizatsiya v tekhnicheskoy podgotovke yunykh konkobezhtsev na etape nachalnoy sportivnoy spetsializatsii [Algorithmization in technical training of young speed skaters at the stage of initial sports specialization] (PhD dissertation). Omsk.
  2. Rogozhnikov, M. A. (2016). Obucheniye yunykh tkhekvondistov bezopornym slozhno-koordinatsionnym tekhnicheskim deystviyam [Teaching young taekwondo practitioners unsupported complex coordination technical actions] (PhD dissertation). St. Petersburg.
  3. Simakov, A. M., Bakulev, S. E., & Chistyakov, V. A. (2014). Aktualnyye voprosy podgotovki v tkhekvondo na nachalnom etape uchebno-trenirovochnogo protsessa [Current issues of training in taekwondo at the initial stage of the educational and training process]. Uchenyye zapiski universiteta im. P.F. Lesgafta, 1(107), 148–150.
  4. Wang, P. (2023). Evaluation and analysis of effectiveness and training process quality based on an interpretable optimization algorithm: The case study of teaching and learning plan in taekwondo sport. Applied Artificial Intelligence, 37(1).
  5. Abhariana, S. E., Abdolvand, N., Abharianc, T. E., & Memari, Z. (2023). Performance prediction of taekwondo athletes using machine learning. Journal of Sports Analytics, 9(3), 378–389.
  6. Shin, M., Lee, D., Chung, A., & Kang, Y. (2023). When Taekwondo Meets Artificial Intelligence. The Development of Taekwondo Techniques. Sports Technology, 7(1), 45–60.
  7. Huipeng, L. (2021). Martial Arts Competitive Decision-Making Algorithm Based on Artificial Intelligence. Journal of Sports Engineering and Technology, 235(4), 513–528.
  8. Pedro, C. (2023). Cyber-Physical System for Evaluation of Taekwondo Athletes. Machines, 11(2), 234–240.