ORGANIZING CONTINUOUS LEARNING IN LMS BASED ON OFFLINE-FIRST ARCHITECTURE AND SECURE TESTING

DOI: 10.31673/2412-4338.2026.019001

Authors

  • Олег Володимирович Барабаш, (Barabash Oleh) National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv https://orcid.org/0000-0003-1715-0761
  • Олена Іванівна Бандурка, (Bandurka Olena) National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv https://orcid.org/0000-0002-8059-1861
  • Ольга Василівна Свинчук, (Svynchuk Olha) National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv https://orcid.org/0000-0001-9032-6335
  • Тарас Русланович Файдюк, (Faidiuk Taras) National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv

Abstract

The article is devoted to the problem of ensuring the continuity and quality of the educational process in Learning Management Systems (LMS) in an environment of unstable internet connection. Synchronization and secure offline testing are vital components of higher education under distance learning conditions, characterized by the absence of a stable power supply and the urgent need to create equal conditions for all learners. These components successfully combine the reliability of traditional methods with the flexibility of information technologies. Given the situation in Ukraine and the unpredictability of the educational process, ensuring the continuous operation of such systems is critical for the efficiency and quality of education at any level. In particular, the main challenges for such systems today are resilience to network and power supply fluctuations, protection against falsification, and ensuring data integrity and authenticity.

The purpose of the study is to develop an architecture for educational data synchronization and secure offline testing in LMS, which ensures educational process continuity under conditions of unstable internet connection, power outages, and dynamic load changes. The primary focus is placed on the Offline-first model, reliable synchronization and state recovery mechanisms, as well as tools for controlling the integrity and authenticity of educational data. The proposed architecture provides for the local storage of critical data and user actions (test responses, progress, educational activity events) with subsequent reconciliation with the server after the connection is restored. To reduce the risks of information loss or tampering, cryptographic verification mechanisms, event logging, and managed versioning are used, allowing for the detection and correct resolution of synchronization conflicts without compromising the quality of the educational process.

Keywords: Learning Management System (LMS), Offline-first model, system architecture, data synchronization, event log, data integrity, version conflicts, cryptographic protection

References

  1. Topuzov, O., Lokshyna, O., & Holovko, M. (2024). Learning losses: the complexity of the problem in the context of the war in Ukraine. Education: Modern Discourses, (6), 7–17. https://doi.org/10.37472/2617-3107-2023-6-01
  2. Hluboka, S. (2024). E-learning: essence, origin and stages of development, features of application in higher education institutions. Current Issues of the Humanities, 76(1), 242-248. https://doi.org/10.24919/2308-4863/76-1-37
  3. Cole, J., & Foster, H. (2007). Using MOODLE: Teaching with the Popular Open Source Course Management System (2nd ed.). O'Reilly Media. https://issuu.com/tparks/docs/moodle
  4. W3C. (2025). Service Workers. Nightly publication history Standards. https://www.w3.org/TR/service-workers
  5. Vasylkivskyi, M., Nikitovych, D., & Boldyrieva, O. (2022). Information data access mana5. gement in intelligent infocommunication networks. Measuring and Computing Devices in Technological Processes, (4), 5-17. https://doi.org/10.31891/2219-9365-2022-72-4-1
  6. Xu, H., Yu, S., Jin, S., Sun, R., Chen, G., & Sun, L. (2024). Enhancing robustness in asynchronous feature tracking for event cameras through fusing frame streams. Complex & Intelligent Systems, 10(2), 6885–6899. https://doi.org/10.1007/s40747-024-01513-0
  7. Shapiro, M., Preguiça, N., Baquero, C., & Zawirski, M. (2011). A comprehensive study of Convergent and Commutative Replicated Data Types (CRDTs). INRIA Research Report No. 7506. https://dsf.berkeley.edu/cs286/papers/crdt-tr2011.pdf
  8. Overeem, M., Spoor, M., & Jansen, S. (2021). An empirical characterization of event-sourced systems and their schema evolution – Lessons from industry. Journal of Systems and Software, 178, 110970. https://doi.org/10.1016/j.jss.2021.110970
  9. W3C. (2025). Web Cryptography Level 2. Standard. https://www.w3.org/TR/webcrypto-2/
  10. Dworkin, M. (2007). Recommendation for Block Cipher Modes of Operation: Galois/Counter Mode (GCM) and GMAC. NIST Special Publication 800-38D. https://doi.org/10.6028/NIST.SP.800-38D
  11. Krawczyk, H., & Eronen, P. (2010). HMAC-based Extract-and-Expand Key Derivation Function (HKDF). RFC 5869. IETF. https://www.rfc-editor.org/rfc/rfc5869
  12. Verkhovna Rada of Ukraine. (2010). Law of Ukraine "On Personal Data Protection". https://zakon.rada.gov.ua/laws/show/2297-17
  13. Schneier, B., & Kelsey, J. (1999). Secure Audit Logs to Support Computer Forensics. ACM Transactions on Information and System Security, 2(2), 159–176. https://dl.acm.org/doi/pdf/10.1145/317087.317089

Published

2026-04-01

Issue

Section

Articles