Software implementation of the Monte Carlo method in Maple as a tool for developing computational skills.

Authors

  • O. Semenikhina Professor of the Department of Computer Science Faculty of Physics and Mathematics Sumy State Pedagogical University named after A. S. Makarenko, Doctor of Pedagogical Sciences, Professor https://orcid.org/0000-0002-3896-8151
  • V. Shamonia Associate Professor, Department of Computer Science, Faculty of Physics and Mathematics, Sumy State Pedagogical University named after A. S. Makarenko, Candidate of Physical and Mathematical Sciences, Associate Professor https://orcid.org/0000-0002-3201-4090
  • M. Soroka Postgraduate student at the Department of Computer Science, Faculty of Physics and Mathematics, Sumy State Pedagogical University named after A. S. Makarenko, Candidate of Physical and Mathematical Sciences, Associate Professor https://orcid.org/0009-0001-2353-692X
  • A. Yurchenko Associate Professor, Department of Computer Science, Faculty of Physics and Mathematics, Sumy State Pedagogical University named after A. S. Makarenko, Candidate of Pedagogical Sciences, Associate Professor https://orcid.org/0000-0002-6770-186X
  • Yu. Khvorostina Associate Professor, Department of Mathematics, Physics, and Teaching Methods Faculty of Physics and Mathematics Sumy State Pedagogical University named after A. S. Makarenko, Candidate of Physical and Mathematical Sciences, Associate Professor https://orcid.org/0000-0002-8354-944X

DOI:

https://doi.org/10.28925/2311-2409.2025.4415

Abstract

The article examines the didactic potential of using the Monte Carlo method within the Maple computer mathematics environment as a means of developing students’ computational skills. It is demonstrated that the software implementation of numerical integration through stochastic methods allows for the effective integration of the content of the courses Numerical Methods and Programming, promoting the development of interdisciplinary competencies, computational thinking, spatial imagination, and skills in critical error analysis.

During the study, a laboratory task was implemented in which students performed the calculation of a double integral using the Monte Carlo method in two ways: by averaging the values of the function over the domain and through the geometric interpretation of the volume under the surface of the function. Both approaches were accompanied by process visualization, which contributed to a better understanding of the method’s essence and the algorithm’s structure.

The use of Maple as a learning tool made it possible to minimize the complexity of algorithm implementation and focus students’ attention on the mathematical and logical content of the problem. The results of pedagogical observation revealed an increase in the substantiation level of students’ actions, an expansion of their ability to independently modify algorithms, and the formation of skills in evaluating the accuracy of results and conducting analytical support for numerical calculations.

The proposed approach is scalable, adaptable to various levels of complexity, and applicable in the training of students in mathematics, engineering, and IT fields. The article also outlines prospects for further research related to the implementation of similar methods in environments such as Python and MATLAB, emphasizing algorithmic thinking and visually oriented learning.

Downloads

Download data is not yet available.

References

Coşkunserçe O. Comparing the use of block-based and robot programming in introductory programming education: Effects on perceptions of programming self-efficacy. Computer Applications in Engineering Education, 2023. Vol. 31(5). Pp. 1234–1255. https://doi.org/10.1002/cae.22637

Khvorostina Yu., Shamonia V., Semenikhina O. The connection between the study of mathematics and programming through the prism of scientific and pedagogical research. Вісник науки та освіти, 2025. Том (4)34. С. 932–945. https://doi.org/10.52058/2786-6165-2025-4(34)-932-945

Ou Q., Liang W., He Z., Liu X., Yang R., Wu X. Investigation and analysis of the current situation of programming education in primary and secondary schools. Heliyon, 2023. Vol. 9(4). No e15530. https://doi.org/10.1016/j.heliyon.2023.e15530

Rudenko Y., Drushlyak M., Osmuk N., Shvets O., Kolyshkin O., Semenikhina O. Problems of Teaching Pupils of Non-Specialized Classes to Program and Ways to Overcome Them: Local Study. International Journal of Computer Science and Network Security, 2022. Vol. 22(1). Pp. 105–112. https://doi.org/10.22937/IJCSNS.2022.22.1.16

Дємєнтьєв Є., Шамоня В., Семеніхіна О. Підготовка IT-фахівців до створення мобільних додатків: огляд актуальних досліджень. Освіта. Інноватика. Практика, 2022. Том 13, №1. С. 7–14. https://doi.org/10.31110/2616-650X-vol13i1-001

Кобильник Т., Когут У., Жидик В. Методичні аспекти вивчення основ алгоритмізації і програмування мовою Python у шкільному курсі інформатики у старших класах. Фізико-математична освіта, 2021. Том 31, №5. С. 36–44. https://doi.org/10.31110/2413-1571-2021-031-5-006

Пенко В., Пенко О. Використання візуалізації на різних етапах вивчення дисципліни «Програмування». Освіта. Інноватика. Практика, 2023. Том 11, №2. С. 31–39. https://doi.org/10.31110/2616-650X-vol11i2-005

Семеніхіна О. В., Руденко Ю. О. Проблеми навчання програмувати учнів старших класів та шляхи їх подолання. Інформаційні технології і засоби навчання, 2018. Том 66(4). С. 54–64.

Чайка В., Ярощук І. Штучний інтелект як засіб створення і реалізації індивідуальних програм розвитку дітей з особливими освітніми потребами. Освіта. Інноватика. Практика, 2025. Том 13, №6. С. 69–79. https://doi.org/10.31110/2616-650X-vol13i6-010

Юрченко А. О., Семеніхіна О. В., Хворостіна Ю. В., Удовиченко О. М. Навчання програмувати в старшій школі крізь призму чинних навчальних програм. Фізико-математична освіта, 2019. Вип. 2(20), Ч.2. С. 47–54.

REFERENCES

Coşkunserçe, O. (2023). Comparing the use of block-based and robot programming in introductory programming education: Effects on perceptions of programming self-efficacy. Computer Applications in Engineering Education, 31(5), 1234–1255. https://doi.org/10.1002/cae.22637

Khvorostina, Yu., Shamonia, V., & Semenikhina, O. (2025). The connection between the study of mathematics and programming through the prism of scientific and pedagogical research. Bulletin of Science and Education, (4)34, 932–945. https://doi.org/10.52058/2786-6165-2025-4(34)-932-945

Ou, Q., Liang, W., He, Z., Liu, X., Yang, R., & Wu, X. (2023). Investigation and analysis of the current situation of programming education in primary and secondary schools. Heliyon, 9(4), e15530. https://doi.org/10.1016/j.heliyon.2023.e15530

Rudenko, Y., Drushlyak, M., Osmuk, N., Shvets, O., Kolyshkin, O., & Semenikhina, O. (2022). Problems of Teaching Pupils of Non-Specialized Classes to Program and Ways to Overcome Them: Local Study. International Journal of Computer Science and Network Security, 22(1), 105–112. https://doi.org/10.22937/IJCSNS.2022.22.1.16

Diemientiev, Ye., Shamonia, V., & Semenikhina, O. (2025). Pidhotovka IT-fakhivtsiv do stvorennia mobilnykh dodatkiv: ohliad aktualnykh doslidzhen [Preparing IT specialists for mobile application creating: a review of current research]. Osvita. Innovatyka. Praktyka – Education. Innovation. Practice, 13(1), 7–14. https://doi.org/10.31110/2616-650X-vol13i1-001 [in Ukrainian]

Kobylnyk, T., Kohut, U., & Zhydyk, V. (2021). Metodychni aspekty vyvchennia osnov alhorytmizatsii i prohramuvannia movoiu Python u shkilnomu kursi informatyky u starshykh klasakh [Methodical aspects of studying the fundamentals of algorithmization and programming language Python school course in informatics in high school]. Fizyko-matematychna osvita – Physical and Mathematical Education, 31(5), 36–44. https://doi.org/10.31110/2413-1571-2021-031-5-006 [in Ukrainian]

Penko, V., & Penko, O. (2023). Vykorystannia vizualizatsii na riznykh etapakh vyvchennia dystsypliny «Prohramuvannia» [Using visualization at different stages of studying the discipline "Programming"]. Osvita. Innovatyka. Praktyka – Education. Innovation. Practice, 11(2), 31–39. https://doi.org/10.31110/2616-650X-vol11i2-005 [in Ukrainian]

Semenikhina, O. V., & Rudenko, Yu. O. (2018). Problemy navchannia prohramuvaty uchniv starshykh klasiv ta shliakhy yikh podolannia [Problems of teaching programming to high school students and ways to overcome them]. Informatsiini tekhnolohii i zasoby navchannia – Information technologies and teaching aids, 66(4), 54–64. [in Ukrainian]

Chaika, V., & Yaroshchuk, I. (2025). Shtuchnyi intelekt yak zasib stvorennia i realizatsii indyvidualnykh prohram rozvytku ditei z osoblyvymy osvitnimy potrebamy [Artificial intelligence as a tool for developing and implementing individual development programs for children with special educational needs]. Osvita. Innovatyka. Praktyka – Education. Innovation. Practice, 13(6), 69–79. https://doi.org/10.31110/2616-650X-vol13i6-010 [in Ukrainian]

Yurchenko, A. O., Semenikhina, O. V., Khvorostina, Yu. V., & Udovychenko, O. M. (2019). Navchannia prohramuvaty v starshii shkoli kriz pryzmu chynnykh navchalnykh prohram [Learning to program in high school through the prism of current curricula]. Fizyko-matematychna osvita – Physical and Mathematical Education, 2(20), 2, 47–54. [in Ukrainian]

Downloads


Abstract views: 14

Published

2025-10-28

How to Cite

Semenikhina , O., Shamonia , V., Soroka , M., Yurchenko , A., & Khvorostina , Y. (2025). Software implementation of the Monte Carlo method in Maple as a tool for developing computational skills. Pedagogical Education: Theory and Practice. Psychology. Pedagogy, (44 (2), 109–116. https://doi.org/10.28925/2311-2409.2025.4415

Issue

Section

Applied aspects of vocational and pedagogical education