Development of professional competencies of students with distance learning technologies in the School-College-University system

Issue 55, 2024

Gulnar Kozhasheva, Yekaterina Gavrilova, Talgat Baidildinov, Aivar Sakhipov, Dinara Zhabykbayeva

Received 25.11.2023, Revised 19.02.2024, Accepted 04.03.2024

https://doi.org/10.54919/physics/55.2024.122nt7

Abstract

Relevance. The relevance of the study lies in presenting the problems faced by participants of the educational process during distance learning, and proposing possible mechanisms for their solution based on global experience. Here, it is necessary to develop a new way of professional implementation of remote technologies, considering modern achievements in science and technology. In addition, it is necessary to ensure the availability of material and technical equipment and the training of qualified specialists.

Purpose. The purpose of the study is to develop a full list of recommendations for the qualitative comprehension of educational material through using distance learning technologies in educational institutions of different levels.

Methodology. The methodology of distance learning is based on conventional approaches to the organisation of the educational process. Theoretical, empirical, statistical and other methods were used to achieve this purpose. In this study, the problem of assessing the quality of distance education in an educational institution was theoretically analysed.

Results. Considering the experience of developed countries, distance learning is applied with some restrictions. These restrictions are related to the level of the educational institution, the educational programme, and other important circumstances. In terms of the academic hours distance learning can be compared with low-residency programme. At the same time, it is possible to study at a convenient time, combining classes with work or homework. Access to quality education, considering its definition within the framework of long-term socio-economic development, is the most important value to citizens.

Conclusions. Distance learning was presented as a conscious, organised, and systematic process of independent control of knowledge, skills, and abilities under the guidance of remote teachers.

Keywords: education; students; research; educational material; distance learning; professional competencies

Suggested citation

Kozhasheva G, Gavrilova Y, Baidildinov T, Sakhipov A, Zhabykbayeva D. Development of professional competencies of students with distance learning technologies in the School-College-University system. Sci Herald Uzhhorod Univ Ser Phys. 2024;(55):1227-1236. DOI: 10.54919/physics/55.2024.122nt7

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References

  1. Weinstein J, Yesin R. Assessment of the formation of professional competencies in the digital environment of the university: scientific publication. Comp Sci Educ. 2020;6:52-60.
  2. Yutkina Yu. Distance education: pros and cons; 2017. http://www.ru-90.ru/content/ю-юткина-дистанционное-образование-плюсы-и-минусы.
  3. Walek B, Ducange P, Hosek O. Designing a tool for evaluating the quality of the teaching-learning workflow of distance learning universities. Advan Intell Syst Comp. 2018;661:358-368.
  4. Zaitseva KV, Vekker VA. Distance learning technologies and their importance for modern vocational education. X International Student Scientific Conference. Student Scientific Forum – 2018; 2018. https://scienceforum.ru/2018/article/2018000426.
  5. Rebysheva L, Vasilchenko E. Problems of distance education at the contemporary stage of development. Modern Prob Sci Educ. 2015;2(2). https://www.science-education.ru/ru/article/view?id=22704.
  6. Baidildinov TZh, Sakhipov AA. Development of an information-resource learning environment with means of interactive interaction. In: Materials of the International Scientific-Practical Conference “Science Today: Theoretical and Practical Aspects” (pp. 54-61). Vologda: LLC “Marker”; 2015.
  7. Costa RD, Souza GF, Valentim RAM, Castro TB. The theory of learning styles applied to distance learning. Cognit Syst Res. 2020;64:134-145.
  8. Bekturganov AE, Maltekbasov MZh, Kalzhanova GK, Kozhasheva GO. The principles of the modular-competence-based approach in the formation of the curriculum of the educational program. Bull APN Kazakh. 2015;3:67-73.
  9. Weindorf-Sysoeva MYe, Gryaznova TS, Shitova VA. Distance learning methodology: textbook for universities. Moscow: Yurayt Publishing House; 2019.
  10. Kozhasheva GO, Zhiembaev Zh, Gavrilova E. On the professional orientation of training future teachers in modern conditions. Sci Life Kazakh. 2019;10:88-95.
  11. Baidildinov TZh, Amankeldikyzy N. Formation of information and communication competence in the professional training of informatics specialists. Repub Sci Methodol J “Electron Sch”. 2015;1:2-4.
  12. Kayser I, Merz T. Lone wolves in distance learning? An empirical analysis of the tendency to communicate within student groups. Int J Mobil Blend Learn. 2020;12(1):82-94.
  13. Polat YeS, Bukharkina MYu, Kondakova ML, Ladyzhenskaya NV, Moiseeva MV, Petrov Aye, Podgornya YeYa. Distance learning pedagogical technologies: a textbook for universities. Moscow: Yurayt Publishing House; 2020.
  14. Gao Y, Zhang SY. Design of and research on autonomous learning system for distance education based on data mining technology. Educ Sci: Theor Pract. 2018;18(6):2633-2640.
  15. Shayakhmetov N. Education values and digitalization; 2020. https://bilimdinews.kz/?p=100030.
  16. Bagci K, Celik HE. Examination of factors affecting continuance intention to use web-based distance learning system via structural equation modelling. Eurasian J Educ Res. 2018;78:43-66.
  17. Kozhakhmetov A, Arynkyzy A, Islyamkhankyzy A. Higher education in the RK: reform cannot be left; 2020. http://bilimdinews.kz/?p=109279.
  18. Traxler J. Distance learning – predictions and possibilities. Educ Sci. 2018;8(1):35.
  19. Robert IV. Theory and methodology of informatization of education (psychological, pedagogical and technological aspects). Moscow: BINOM. Knowledge laboratory; 2014.
  20. Lingard B. Globalization and education. London: Routledge; 2020.
  21. Weinstein J. Problems of the development of distance education. Sci Time. 2014;10:64-70.
  22. Opiq. 2017. https://www.opiq.kz.
  23. Karibayeva B, Kunanbayeva S. Kazakh power distance dimension in business discourse. Soc Semiot. 2018;28(2):286-296.
  24. Kunanbayeva SS. Educational paradigm: Implementation of the competence-based approach to the higher school system. Int J Environ Sci Educ. 2016;11(18):12699-12710.
  25. Pirahandeh M, Kim D-H. Co-designing an intelligent doctors-colleagues-patients social network. Proceed - Int Conf Cloud Comput Soc Network 2012: Cloud Comput Soc Network Smart Product Soc ICCCSN 2012. 2012;1:6215739. https://doi.org/10.1109/ICCCSN.2012.6215739.
  26. Balykbayev T, Issabayeva D, Rakhimzhanova L, Zhanysbekova S. Distance learning at KazNPU Named after Abai: Models and Technologies. In: SIST 2021 - 2021 IEEE International Conference on Smart Information Systems and Technologies (article number: 9465980). Nur-Sultan: Institute of Electrical and Electronics Engineers; 2021.
  27. Zhampeisova K, Balykbayev T, Khan N, Kolumbayeva S. The content of the professional training of the teacher in Kazakhstan. Opcion. 2018;34(Special Issue 14):683-710.
  28. Chuprun N, Shulga M. Optimization of motor activity of youth students using the asics runkeeper mobile application in the conditions of distance education. Theory Pract Physic Cult Sports. 2023;3:110-116. https://doi.org/10.31470/2786-6424-1/2023-110-116.
  29. Nazemi K, Burkhardt D, Ginters E, Kohlhammer J. Semantics visualization – definition, approaches and challenges. Proced Comp Sci. 2015;75:75-83.
  30. Ginters E, Aizstrauta D. Technologies sustainability modeling. Adv Intell Syst Comput. 2018;746:659-668.
  31. Aizstrauta D, Ginters E. Introducing integrated acceptance and sustainability assessment of technologies: A model based on system dynamics simulation. Lect Notes Busin Inform Process. 2013;145:23-30.
  32. Tulkinbekov K, Pirahandeh M, Kim D-H. _Coalesced Leveldb for Small Data. Int Conf Ubiquit Future Networks, ICUFN. 2019;2019-July:567-569.
  33. Pirahandeh M, Kim D-H. MS scheduler: New, scalable, and high-performance sparse AVX-2 parity encoding and decoding technique for erasure-coded cloud storage systems. Future Gener Comp Syst. 2022;126:123-135.
  34. Balykbayev T, Bidaibekov E, Grinshkun V, Kurmangaliyeva N. The influence of interdisciplinary integration of information technologies on the effectiveness of IT training of future teachers. J Theor Appl Inform Technol. 2022;100(5):1265-1274.
  35. Sharipova S, Аkanova A, Ospanova N. Development of a neural network model for training data on the effects of phosphorus on spring wheat growth. East-Eur J Enterp Technol. 2023;6(4(126)):32-38.
  36. Nestulya S, Shara S. Distance learning as a relevant educational technology in higher education institutions. Sci Bull Mukach State Univer. Seri “Ped Psychol”. 2023;9(1):39-46. https://doi.org/10.52534/msu-pp1.2023.39.
  37. Pirahandeh M, Kim D-H. A New Energy-Aware GPU Based Erasure Coding Scheduler for Cloud Storage Systems. Int Conf Ubiquit Future Networks, ICUFN. 2018;2018-July:619-621.
  38. Ahn C, Pirahandeh M, Kim D-H. Dynamic allocation of replication and erasure codes for enhancing storage efficiency in openstack swift. In: 2020 International Conference on Electronics, Information, and Communication, ICEIC 2020 (article number: 9051133). Barcelona: Institute of Electrical and Electronics Engineers; 2020.
  39. Ginters E. New trends towards digital technology sustainability assessment. In: Proceedings of the World Conference on Smart Trends in Systems, Security and Sustainability, WS4 2020 (pp. 184–189). Virtual, London: Institute of Electrical and Electronics Engineers; 2020.
  40. Ginters E, Dimitrovs E. Latent Impacts on Digital Technologies Sustainability Assessment and Development. Adv Intell Syst Comput. 2021;1365 AIST:3-13.
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