Analysis of motivation determinants in the implementation of online training of future managers at state universities
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- Category: Content №3 2023
- Last Updated on 27 June 2023
- Published on 30 November -0001
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Authors:
V.H.Fatkhutdinov, orcid.org/0000-0003-1231-5379, Interregional Academy of Personnel Management, Kyiv, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
B.H.Amarathunga*, orcid.org/0000-0003-3837-9979, Wayamba University of Sri Lanka, Kuliyapitiya, the Democratic Socialist Republic of Sri Lanka, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
V.S.Nitsenko, orcid.org/0000-0002-2185-0341, Ivano-Frankivsk National Technical Oil and Gas University, Ivano-Frankivsk, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
D.B.Svyrydenko, orcid.org/0000-0001-6126-1747, Dragomanov Ukrainian State University, Kyiv, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
V.V.Kotsur, orcid.org/0000-0001-6647-7678, Hryhorii Skovoroda University in Pereiaslav, Pereiaslav, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
* Corresponding author e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2023, (3): 171 - 176
https://doi.org/10.33271/nvngu/2023-3/171
Abstract:
Purpose. Improvement of the quality of online education of university students, taking into account their motivational component.
Methodology. The research results were obtained using general and special methods of cognition: abstract-logical, analysis, systematization and combination, the method of theoretical generalization, deduction and induction, statistical analysis.
Findings. A study on a sample of 377 undergraduate students majoring in “Management” in Sri Lanka demonstrated a good fit of the proposed structural equation model to the observed data, confirming that content and organization, Internet access, and service quality had statistically significant effects on online learning.
Originality. With the recombination of variables, the possibility of ensuring an increase in the quality of education is formed due to the effective increase of a significant motivational component of the educational process
Practical values. The results of the study are useful for all participants in the education sector. They offer a guideline for university administrations on how they should conduct online teaching, ensuring the effectiveness of the learning process, taking into account the motivational component
Keywords: undergraduate students majoring in “Management”, motivation factors, online learning, students’ satisfaction, state universities
References:
1. Turban, E., King, D., Lee, J. K., Liang, T.-P., & Turban, D. C. (2015). Electronic Commerce: A Managerial and Social Networks Perspective, 8. Springer Cham. https://doi.org/10.1007/978-3-319-10091-3.
2. Revin, F. (2021). The Shifting Image of Social Capital: Digitizing Cooperative Ties. Future Human Image, 16, 75-82. https://doi.org/10.29202/fhi/16/7.
3. Fatkhutdinova, O. (2018). Impact of Legal Education on the Development of Space Law. Advanced Space Law, 1, 42-49. https://doi.org/10.29202/asl/2018/1/5.
4. Terepyshchyi, S. (2022). The Interaction of Education and the Global Social System: the Experience of China. Ukrainian Policymaker, 10, 37-42. https://doi.org/10.29202/up/10/5.
5. Lin, G. T. R., & Sun, C. (2009). Factors influencing satisfaction and loyalty in online shopping: an integrated model. Online Information Review, 33(3), 458-475. https://doi.org/10.1108/14684520910969907.
6. Szymanski, D. M., & Hise, R. T. (2000). E-satisfaction: an initial examination. Journal of Retailing, 76(3), 309-322. https://doi.org/10.1016/S0022-4359(00)00035-X.
7. Sureshchandar, G. S., Rajendran, C., & Anantharaman, R. N. (2002). The relationship between service quality and customer satisfaction – a factor specific approach. Journal of Services Marketing, 16(4), 363-379. https://doi.org/10.1108/08876040210433248.
8. Bauk, S., Šćepanović, S., & Kopp, M. (2014). Estimating Students’ Satisfaction with Web Based Learning System in Blended Learning Environment. Education Research International, 2014, 731720. https://doi.org/10.1155/2014/731720.
9. Alsabawy, A. Y., Cater-Steel, A., & Soar, J. (2013). IT infrastructure services as a requirement for e-learning system success. Computers & Education, 69, 431-451. https://doi.org/10.1016/j.compedu.2013.07.035.
10. Rapanta, C., Botturi, L., Goodyear, P., & Koole, M. (2020). Online University Teaching During and After the Covid-19 Crisis: Refocusing Teacher Presence and Learning Activity. Postdigital Science and Education, 2, 923-945. https://doi.org/10.1007/s42438-020-00155-y.
11. Sun, J. C., & Rueda, R. (2012). Situational Interest, Computer Self-Efficacy and Self-Regulation: Their Impact on Student Engagement in Distance Education. British Journal of Educational Technology, 43, 191-204. https://doi.org/10.1111/j.1467-8535.2010.01157.x.
12. Kolb, D. A., & Kolb, A. Y. (2013). The Kolb Learning Style Inventory 4.0: Guide to Theory, Psychometrics, Research & Applications. Experience Based Learning Systems.
13. Muhammad, A., Zhou, Q., Beydoun, G., Xu, D., & Shen, J. (2016). Learning path adaptation in online learning systems. In: 2016 IEEE 20 th International Conference on Computer Supported Cooperative Work in Design (CSCWD), (pp. 421-426). United States: IEEE. https://doi.org/10.1109/CSCWD.2016.7566026.
14. Wu, J.-H., Tennyson, R. D., & Hsia, T.-L. (2010). A study of student satisfaction in a blended e-learning system environment. Computers and Education, 55, 155-164. https://doi.org/10.1016/j.compedu.2009.12.012.
15. Wade-Benzoni, K. A., Rousseau, D. M., & Li, M. (2006). Managing relationships across generations of academics. International Journal of Conflict Management, 17(1), 4-33. https://doi.org/10.1108/10444060610734154.
16. Chowdhury, S., Rahman, M., Doddanavar, I. A., Zayed, N. M., Nitsenko, V., Melnykovych, O., & Holik, O. (2023). Impact of Social Media on Knowledge of the COVID-19 Pandemic on Bangladeshi University Students. Computation, 11, 38. https://doi.org/10.3390/computation11020038.
17. Arora, B. (2019). Teaching cyber security to non-tech students. Politics, 39(2), 252-265. https://doi.org/10.1177/0263395718760960.
18. Mahyoob, M. (2020). Challenges of e-Learning during the COVID-19 Pandemic Experienced by EFL Learners. Arab World English Journal, 11(4) 351-362. https://doi.org/10.24093/awej/vol11no4.23.
19. Alturise, F. (2020). Evaluation of Blackboard Learning Management System for Full Online Courses in Western Branch Colleges of Qassim University. International Journal of Emerging Technologies in Learning, 15(15), 33-51. https://doi.org/10.3991/ijet.v15i15.14199.
20. Pham, L., Limbu, Y. B., Bui, T. K., Nguyen, H. T., & Pham, H. T. (2019). Does e-learning service quality influence e-learning student satisfaction and loyalty? Evidence from Vietnam. International Journal of Educational Technology in Higher Education, 16, 7. https://doi.org/10.1186/s41239-0190136-3.
21. Levin, T., & Wadmany, R. (2006). Teachers’ Beliefs and Practices in Technology-based Classrooms. A Developmental View. Journal of Research on Technology in Education, 39(2), 157-181. https://doi.org/10.1080/15391523.2006.10782478.
22. Winberg, T., & Hedman, L. (2008). Student attitudes toward learning, level of pre knowledge and instruction type in a computer-simulation: effects on flow experiences and perceived learning outcomes. Instructional Science, 36(4), 269-287. Retrieved from http://www.jstor.org/stable/23372883.
23. Sintema, E. J. (2020). Effect of COVID-19 on the Performance of Grade 12 Students: Implications for STEM Education. EURASIA Journal of Mathematics, Science and Technology Education, 16(7), em1851. https://doi.org/10.29333/ejmste/7893.
24. Ivanov, D. (2020). Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case. Transportation Research Part E: Logistics and Transportation Review, 136, 101922. https://doi.org/10.1016/j.tre.2020.101922.
25. Owusu-Fordjour, C., Koomson, C. K., & Hanson, D. (2020). The impact of covid-19 on learning the perspective of the Ghanaian student. European Journal of Education Studies, 7(3). https://doi.org/10.46827/ejes.v0i0.3000.
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