Development and evaluation of the effectiveness of the integration gateway for the interaction of the learning management system with external systems and services of state information systems

Authors

DOI:

https://doi.org/10.15587/1729-4061.2022.258089

Keywords:

integration gateway, learning management system, integration service, representative transfer technology

Abstract

The paper presents the results of the development of information technology for the interaction of the learning management system with the state information systems of the Republic of Kazakhstan in the field of higher education. Integration with these systems is based on the integration gateway, which is part of the educational portal of the East Kazakhstan Technical University named after D. Serikbayev. Approaches to organizing data exchange with external information systems were analyzed and described, and mechanisms for integrating the national database of the Republic of Kazakhstan with a unified higher education management system were identified. The created integration gateway within the framework of the educational portal interacts with the information systems using the technology of transferring a representative state, data transfer is carried out in text format. The implemented gateway allows you to receive the necessary data from the database of the educational portal, generate data packets for transmission, connect to an external system and transfer data. To evaluate the efficiency of the gateway, computational experiments were carried out in which data of various volumes were transferred through the created gateway to state information systems and the time of their transmission was recorded. Based on the obtained data, the dependences of the transmission time on the amount of transmitted data for each information system with which interaction is carried out were obtained and their graphical display was built. According to the results of the experiments, it was shown that the transmission time has a polynomial dependence on the amount of data, which makes it possible to interact with the indicated information systems in real time

Supporting Agency

  • The study is carried out within the framework of the project funded by the Ministry of Education and Science of the Republic of Kazakhstan AP08856846

Author Biographies

Yevgeniy Fedkin, D. Serikbayev East Kazakhstan Technical University

Doctoral Student

Department of Information Technology

Saule Kumargazhanova, D. Serikbayev East Kazakhstan Technical University

Candidate of Technical Sciences, Associate Professor

School of Information Technology and Intelligent Systems

Natalya Denissova, D. Serikbayev East Kazakhstan Technical University

Candidate of Physical and Mathematical Sciences, Associate Professor, Member of the Board ‑ Vice-Rector for Research and Digitalization

Saule Smailova, D. Serikbayev East Kazakhstan Technical University

PhD, Associate Professor

School of Information Technology and Intelligent Systems

Saule Rakhmetullina, D. Serikbayev East Kazakhstan Technical University

Candidate of Technical Sciences, Associate Professor, Member of the Board ‑ Vice-Rector for Development Strategy

Lazzat Kakisheva, D. Serikbayev East Kazakhstan Technical University

Department of Information Technology

Iurii Krak, Taras Shevchenko National University of Kyiv

Doctor of Physical and Mathematical Sciences, Professor

Department of Theoretical Cybernetics

References

  1. Calvert, C. E. (2014). Developing a model and applications for probabilities of student success: a case study of predictive analytics. Open Learning: The Journal of Open, Distance and e-Learning, 29 (2), 160–173. doi: https://doi.org/10.1080/02680513.2014.931805
  2. Kuzilek, J., Hlosta, M., Herrmannova, D., Zdrahal, Z., Vaclavek, J., Wolff, A. (2015). OU Analyse: analysing at-risk students at The Open University. Learning Analytics Review, LAK15-1, 1–16. Available at: http://oro.open.ac.uk/42529/
  3. Herodotou, C., Rienties, B., Hlosta, M., Boroowa, A., Mangafa, C., Zdrahal, Z. (2020). The scalable implementation of predictive learning analytics at a distance learning university: Insights from a longitudinal case study. The Internet and Higher Education, 45, 100725. doi: https://doi.org/10.1016/j.iheduc.2020.100725
  4. IHEP. Available at: https://www.ihep.org/about-ihep/
  5. Wolf, M., Taimuty, M., Patel, M., Meteyer, J. (2016). The Dean’s information challenge: from data to dashboard. EduCause Review. Available at: https://er.educause.edu/articles/2016/11/the-deans-information-challenge-from-data-to-dashboard
  6. The Ed Tech Revolution is About to Become the Learner Revolution (2014). Education Design Lab. Available at: https://eddesignlab.org/resources/the-ed-tech-revolution-is-about-to-become-the-learner-revolution-2014/
  7. Adams, B. S., Cummins, M., Davis, A., Freeman, A., Hall Giesinger, C., Anantha-Narayanan, V. (2017). NMC horizon report: 2017 higher education edition. Austin, Texas: The New Media Consortium.
  8. Williamson, B. (2018). The hidden architecture of higher education: building a big data infrastructure for the “smarter university.” International Journal of Educational Technology in Higher Education, 15 (1). doi: https://doi.org/10.1186/s41239-018-0094-1
  9. Heidi Plus: Higher education business intelligence. Available at: https://www.hesa.ac.uk/services/heidi-plus
  10. Roberson, A. J., Roriso, J., Voight, M. (2017). A blueprint for better information: Recommendations for a federal postsecondary student-level data network. Washington, DC: Institute for Higher Education Policy. Available at: https://www.ihep.org/publication/a-blueprint-for-better-information-recommendations-for-a-federal-postsecondary-student-level-data-network/
  11. Serikbayeva, S., Tussupov, J., Sambetbayeva, M., Yerimbetova, A., Sadirmekova, Z., Tungatarova, A. et. al. (2021). Development of a model and technology of access to documents in scientific and educational activities. Eastern-European Journal of Enterprise Technologies, 6 (2 (114)), 44–58. doi: https://doi.org/10.15587/1729-4061.2021.248506
  12. Fedkin, E., Denissova, N., Krak, I., Dyomina, I. (2021). Automation of Scheduling Training Sessions in Educational Institutions using Genetic Algorithms. 2021 11th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS). doi: https://doi.org/10.1109/idaacs53288.2021.9660939
  13. Shor, A. M. (2020). Comparative analysis of approaches in the development of API web applications. StudNet, 3 (9), 533–540.
  14. Kuznetsova, R. V. (2020). Problems of integration of information systems on the platform "1C: Enterprise 8" with external information systems. Russian science: trends and opportunities: collection of scientific articles. Moscow: Publishing House "Pero", 100–104.
  15. Zuev, V., Kakisheva, L., Denissova, N., Kumargazhanova, S., Smailova, S. (2021). Development of a Set of Requirements for the Hardware and Software of LMS Services of the University. International Journal of Emerging Technologies in Learning (iJET), 16 (21), 210. doi: https://doi.org/10.3991/ijet.v16i21.25239
  16. Kumargazhanova, S., Erulanova, A., Soltan, G., Suleimenova, L., Zhomartkyzy, G. (2018). System of indicators for monitoring the activities of an educational institution. 2018 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT). doi: https://doi.org/10.1109/usbereit.2018.8384580

Downloads

Published

2022-06-30

How to Cite

Fedkin, Y., Kumargazhanova, S., Denissova, N., Smailova, S., Rakhmetullina, S., Kakisheva, L., & Krak, I. (2022). Development and evaluation of the effectiveness of the integration gateway for the interaction of the learning management system with external systems and services of state information systems . Eastern-European Journal of Enterprise Technologies, 3(2 (117), 30–38. https://doi.org/10.15587/1729-4061.2022.258089

Issue

Vol. 3 No. 2 (117) (2022): Information technology. Industry control systems

Section

Information technology

License

Copyright (c) 2022 Yevgeniy Fedkin, Saule Kumargazhanova, Natalya Denissova, Saule Smailova, Saule Rakhmetullina, Lazzat Kakisheva, Iurii Krak

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.

A license agreement is a document in which the author warrants that he/she owns all copyright for the work (manuscript, article, etc.).
The authors, signing the License Agreement with TECHNOLOGY CENTER PC, have all rights to the further use of their work, provided that they link to our edition in which the work was published.
According to the terms of the License Agreement, the Publisher TECHNOLOGY CENTER PC does not take away your copyrights and receives permission from the authors to use and dissemination of the publication through the world's scientific resources (own electronic resources, scientometric databases, repositories, libraries, etc.).
In the absence of a signed License Agreement or in the absence of this agreement of identifiers allowing to identify the identity of the author, the editors have no right to work with the manuscript.
It is important to remember that there is another type of agreement between authors and publishers – when copyright is transferred from the authors to the publisher. In this case, the authors lose ownership of their work and may not use it in any way.