TECHNOLOGICAL CHALLENGES IN DEVELOPING A PLATFORM FOR MASSIVE OPEN ONLINE COURSES
https://doi.org/10.47649/vau.26.v80.i1.12
Abstract
The development and use of massive open online courses (MOOC) platforms are associated with some complex technological issues that affect the quality of learning and the availability of educational content. The main technological issues can be divided into several areas: platform interoperability and integration, the introduction of artificial intelligence (AI) and chatbots, scalability and data processing, multilingualism and localization, and security and legal aspects. The Learning Tools Interoperability (LTI) standard is often used to ensure interoperability between learning management systems (LMS), but during implementation, problems arise with synchronizing user accounts and assigning grades. The introduction of AI increases support for learners, but poses risks such as limited contextual understanding, decision inauthenticity (XAI), and technological hallucinations. The platforms require processing large amounts of data (clicks, logs, test results), leading to server overload and necessitating specialized servers such as Milvus. Multilingualism issues arise from machine translation errors, especially in technical terms, while security concerns include GDPR compliance and copyright management. This study is a systematic literature review and is based on an analysis of 27 scientific articles published between 2020 and 2026, including an additional 7 scientific articles on this topic indexed in the Scopus database These articles address technological solutions to the problems, including RAG technology, knowledge graphs (EduKGs), and human-in-the-loop approaches. In addition, 20 articles were included in the proceedings of the international scientific conference “European MOOCs Stakeholder Summit – EMOOCS 2025”, which will be held at the Université Télécom Paris, Palaiseau, France, from 30 June to 2 July 2025 The results demonstrate the interrelationship of technological and pedagogical factors in the development of HELC platforms, and on this basis allow for increasing the effectiveness of education.
Keywords
About the Authors
N. OspanovaKazakhstan
Nazira Ospanova - Candidate of Pedagogical Sciences, Associate Professor, Faculty of Computer Science,
Pavlodar
N. Tokzhigitova
Russian Federation
Nurgul Tokzhigitova - PhD, Associate Professor, Faculty of Computer Science,
Pavlodar
S. Baizhumanov
Kazakhstan
Saduakas Baizhumanov, senior lecturer,
Pavlodar
R. Kuanysheva
Kazakhstan
Raushan Kuanysheva, senior lecturer at the Faculty of Computer Science,
Pavlodar
References
1. Jansen R.S. Jappai aşyq onlain kurstarda bılım aluşylardyñ özın-özı retteitın oqytuyn qoldau [Jansen, R. S. Supporting learners’ self-regulated learning in Massive Open Online Courses] R. S. Jansen, A. van Leeuwen, J. Janssen et al. // Computers & Education. - 2020. - Vol. 146. - Art. 103771 р. [in Kazakh]
2. Zhou L. I-DEMATEL-ISM ädısı negızınde JAOK sapasyna äser etetın faktorlardy taldau. [ Analysis of factors influencing MOOC quality based on I-DEMATEL-ISM method] L. Zhou, M. Tang, J. Liu // Systems and Soft Computing. - 2025. - Vol. 7. - Art. 200220-р. [in Kazakh]
3. Haugsbakken, H. SPOC jasaudağy generativtıjasandy intelekttıñ rölı: Işınara jasandy intelekt jasağan oqu resurstaryn studentterdıñ qabyldauy [The Role of Generative AI in SPOC-Making: Student Perception of Partially AIGenerated Learning Resources] H. Haugsbakken, M. Hagelia, I. Nagel // EMOOCS 2025: Proceedings / ed. by E. Hamonic, R. Sharrock. – Cham: Springer, 2026. – (LNCS, vol. 15733). – P. 3–13. [in Kazakh]
4. Brünner B. JAOK-tardağy GenAI chatbottaryn zertteu: studentterdıñ özara ärekettesuın jäne özın-özı retteitın oqu mınez-qūlqyn taldau [ Exploring GenAI Chatbots in MOOCs: Analyzing Student Interactions and Self-regulated Learning Behaviors] / B. Brünner, M. Ebner, S. Schön // EMOOCS 2025: Proceedings / ed. by E. Hamonic, R. Sharrock. – Cham: Springer, 2026. – (LNCS, vol. 15733). – P. 14–24. [in Kazakh]
5. Thammetar T. Avtomattandyrylğan oqytudy qoldau üşın generativtı jasandy intelektpen jūmys ısteitın chatbotty integrasialau:Tai JAOK platformasynyñ täjıribesı [The Integration of Generative AI-Powered Chatbot for Automated Learning Support: Thai MOOC Platform Experience]/ T. Thammetar, A. Theeraroungchaisri, J. Khlaisang et al. // EMOOCS 2025: Proceedings / ed. by E. Hamonic, R. Sharrock. – Cham: Springer, 2026. – (LNCS, vol. 15733). – P. 25–35 [in Kazakh]
6. Moreno-Marcos P. M. edX boiynşa Java JAOK seriasyndağy oquşylardyñ tabysty boljau modelderın jalpylaudy taldau [Analysis of the Generalization of Students’ Success Predictive Models in a Series of Java MOOCs on edX] / P. M. Moreno-Marcos, M. R. Guillén, C. Alario-Hoyos et al. // EMOOCS 2025: Proceedings / ed. by E. Hamonic, R. Sharrock. – Cham: Springer, 2026. – (LNCS, vol. 15733). – P. 36–45. [in Kazakh]
7. Maldonado-Mahauad J. Strategialyq jäne keşendı: Oqu tızbekterın üderıstık öndıru arqyly JAOK oquşysynyñ mınez-qūlqyn modeldeu [ Strategic and Comprehensive: Modeling MOOC Learner Behavior Through Process Mining of Learning Sequences] / J. Maldonado-Mahauad // EMOOCS 2025: Proceedings / ed. by E. Hamonic, R. Sharrock. – Cham: Springer, 2026. – (LNCS, vol. 15733). – P. 46–59. [in Kazakh]
8. Stancin K. Studentterdıñ onlain kurstardağy qajettılıkterı men ümıtterın olardyñ qatysuy men oqu täjıribesın jaqsartu üşınqalai tüsınuge bolady? [How Can We Understand Students’ Needs and Expectations in Online Courses to Improve Their Engagement and Learning Experience?] / K. Stancin, D. Jaksic, A. Petrovic // EMOOCS 2025: Proceedings / ed. by E. Hamonic, R. Sharrock. – Cham: Springer, 2026. – (LNCS, vol. 15733). – P. 60–71. [in Kazakh]
9. Wolf, D. Maman emes mūğalımder men oquşylardy kodtau boiynşa mümkındıktermen qamtamasyz etu: Avstria orta mektebındegı Python JAOK-tyñ jağdailyq zertteuı [Empowering Non-specialist Teachers and Students in Coding: A Case Study of a Python MOOC in an Austrian High School] / D. Wolf, M. Ebner // EMOOCS 2025: Proceedings / ed. by E. Hamonic, R. Sharrock. – Cham: Springer, 2026. – (LNCS, vol. 15733). – P. 72–85. [in Kazakh]
10. Ferrari S. Özındık qarqynmen damytylatyn JAOK-tardan tys onlain qauymdastyqty qaita oilastyru [Rethinking Online Community Beyond Self-paced MOOCs] / S. Ferrari, A. Merigo // EMOOCS 2025: Proceedings / ed. by E. Hamonic, R. Sharrock. – Cham: Springer, 2026. – (LNCS, vol. 15733). – P. 86–97. [in Kazakh]
11. Sofyan Z. Jasandy intelekttı masştabta oqytu turaly tüsınıkter: oquşyğa bağyttalğan jetıldıru üşın derekterge negızdelgen kerı bailanys [Insights on Teaching AI at Scale: Data-Driven Feedback for Learner-Centered Improvement] / Z. Sofyan, C. Meinel // EMOOCS 2025: Proceedings / ed. by E. Hamonic, R. Sharrock. – Cham: Springer, 2026. – (LNCS, vol. 15733). – P. 98–107. [in Kazakh]
12. Abdelmagied M. JAOK-ta oquşylardyñ bılım ūğymdaryn tüsınuın qoldau üşın grafiktı ızdeu arqyly keñeitılgen ūrpaqty paidalanu [Leveraging Graph Retrieval-Augmented Generation to Support Learners’ Understanding of Knowledge Concepts in MOOCs] / M. Abdelmagied, M. A. Chatti, S. Joarder et al. // EMOOCS 2025: Proceedings / ed. by E. Hamonic, R. Sharrock. – Cham: Springer, 2026. – (LNCS, vol. 15733). – P. 108–118 [in Kazakh]
13. Ain, Q. U. CourseMapper-de bılım beru bılımınıñ grafigın avtomatty türde qūru üşın joğarydan tömen jäne tömennen joğary täsılder [Top-Down vs. Bottom-Up Approaches for Automatic Educational Knowledge Graph Construction in CourseMapper] / Q. U. Ain, M. A. Chatti, A. Shakhshir et al. // EMOOCS 2025: Proceedings / ed. by E. Hamonic, R. Sharrock. – Cham: Springer, 2026. – (LNCS, vol. 15733). – P. 119–129. [in Kazakh]
14. Minaeva E. A. JAOK halyqaralyq studentterdı tartu qūraly retınde: elderaralyq taldau [MOOCS as a Tool for International Student Recruitment: A Cross-Country Analysis] / E. A. Minaeva, U. S. Zakharova, S. V. Zhuchkova // EMOOCS 2025: Proceedings / ed. by E. Hamonic, R. Sharrock. – Cham: Springer, 2026. – (LNCS, vol. 15733). – P. 130–143. [in Kazakh]
15. Staubitz T. Öz tağamyñyzdy jeu - aşyq edX latformasyndağy jobağa negızdelgen oqu eksperimentı [Eating Your Own Dogfood - A Project-Based Learning Experiment on an Open edX Platform ]/ T. Staubitz, S. Trabucchi, E. Huthmacher // EMOOCS 2025: Proceedings / ed. by E. Hamonic, R. Sharrock. – Cham: Springer, 2026. – (LNCS, vol. 15733). – P. 147–157. [in Kazakh]
16. Reda V. Bılımdegı olqylyqtardy joiu: JAOK-tardyñ saiasi ğylymdar bılımı üşın äleuetı [Bridging Knowledge Gaps: The Potential of MOOCs for Political Science Education ]/ V. Reda, A. Squillante // EMOOCS 2025: Proceedings / ed. by E. Hamonic, R. Sharrock. – Cham: Springer, 2026. – (LNCS, vol. 15733). – P. 158–167 [in Kazakh]
17. Ebner M. Europalyq universitetter odaqtarynda jasandy intelekt, LTI jäne aşyq lisenzialardyñ kömegımen köptıldı JAOK-tardyengızu: tehnikalyq jäne ūiymdastyruşylyq qiyndyqtar [Implementing Multilingual MOOCs in European University Alliances with the Help of AI Usage, LTI and Open Licenses: Technical and Organizational Challenges ]/ M. Ebner, S. Schön, K. Gasplmayr et al. // EMOOCS 2025: Proceedings / ed. by E. Hamonic, R. Sharrock. – Cham: Springer, 2026. – (LNCS, vol. 15733). – P. 168–178. [in Kazakh]
18. Esteves F. d. L. Sifrlyq oqytu arqyly tūraqtylyq turaly habardarlyqty arttyru: barlyq jañadan qabyldanğan studentterge arnalğan institusionaldyq SPOC, JAOK közqarasyna qarai jylju [ Raising Awareness on Sustainability Through Digital Learning: An Institutional SPOC for All Newly Admitted Students, Moving Towards a MOOC Perspective] / F. d. L. Esteves, E. Maes, B. Mayeur et al. // EMOOCS 2025: Proceedings / ed. by E. Hamonic, R. Sharrock. – Cham: Springer, 2026. – (LNCS, vol. 15733). – P. 179–189 [in Kazakh]
19. Feistmantl E. Bes jyldan astam uaqyt ötkennen keiın pänaralyq universitettık kursqa Covid-19 aldyndağy JAOK engızu jäne bağalau:E-Tutoring@UIBK jäne MekoMOOC, Case Study [ Embedding and Evaluating a Pre-Covid-19 MOOC in an Interdisciplinary University Course More Than Five Years Later: E-Tutoring@UIBK and the MekoMOOC, A Case Study] / E. Feistmantl // EMOOCS 2025: Proceedings / ed. by E. Hamonic, R. Sharrock. – Cham: Springer, 2026. – (LNCS, vol. 15733). – P. 190–199. [in Kazakh]
20. Engeness I. Bılım beruşılerge arnalğan jasandy intelekt chatbottary: joğary bılım berude onlain oqytudy özgertu [AI Chatbots for Educators: Transforming Online Learning in Higher Education / I. Engeness, M. Nohr, T. Fossland] // EMOOCS 2025: Proceedings / ed. by E. Hamonic, R. Sharrock. – Cham: Springer, 2026. – (LNCS, vol. 15733). – P. 200–210 [in Kazakh]
21. Despujol Zabala I. Avtomattandyrylğan model men parametrlerdı tañdau üşın LLM paidalanyp, ispan tılınde endıruge negızdelgen beine ūsynysyn oñtailandyru [Optimizing Embedding-Based Video Recommendation in Spanish Using LLMs for Automated Model and Parameter Selection]/ I. Despujol Zabala, C. Turró Ribalta, J. Busquets Mataix et al. // EMOOCS 2025: Proceedings / ed. by E. Hamonic, R. Sharrock. – Cham: Springer, 2026. – (LNCS, vol. 15733). – P. 211–221 [in Kazakh]
22. Sancassani S. AIBook JAOK arqyly dialogtyq oqytudağy jaña şekara retınde: Case [The AIBook as a New Frontier in Conversational Learning Through a MOOC: A Case Study] / S. Sancassani, D. Casiraghi // EMOOCS 2025: Proceedings / ed. by E. Hamonic, R. Sharrock. – Cham: Springer, 2026. – (LNCS, vol. 15733). – P. 222–231 [in Kazakh]
23. Onan A. Jappai aşyq onlain kurstardy bağalaudağypıkırlerge sentimenttık taldau: mätındık maining jäne tereñ oqytu täsılı [Sentiment analysis on massive open online course evaluations: A text mining and deep learning approach] / A. Onan // Computer Applications in Engineering Education. - 2021. - Vol. 29, iss. 3. - P. 572–589 [in Kazakh]
24. Adnan M. Maşinalyq oqytu modelderın paidalana otyryp, kurstyñ ärtürlı kezeñderınde erte aralasu üşın täuekel tobyndağy studentterdı boljau [Predicting at-Risk Students at Different Percentages of Course Length for Early Intervention Using Machine Learning Models ]/ M. Adnan, A. Habib, J. Ashraf et al. // IEEE Access. - 2021. - Vol. 9. - P. 149464–149478 [in Kazakh]
25. Al-Lahlali, B. Maşinalyq oqytu ädısterın qoldanuarqyly studentterdıñ ülgerımın boljau: jüielı ädebi şolu [AlLahlali, B. Predicting student performance using ML techniques: a systematic literature review] / B. Al-Lahlali, H. Alashwal // Education Sciences. - 2021. - Vol. 11, iss. 9. - Art. 552-р [in Kazakh]
26. Alghamdi, A. Mätındık maining jäne tereñ oqytu ädısterın qoldana otyryp, JAOK-ta bırlesken süzgılerdıñ däldıgın arttyru üşın äleumettık derekterdı taldau [Alghamdi, A. Analysis of social data for accuracy improvement of collaborative filtering in MOOCs using text mining and deep learning techniques] / A. Alghamdi, M. Nilashi, R. A. Abumalloh et al. // Discover Computing. - 2025. - Vol. 28. - Art. 33-р[in Kazakh]
27. Ruiz-Rojas L. I. Generativtı jasandy intelekt qūraldary arqyly bılım berudı küşeitu: oqu dizainy matrisasy negızındegı täsıl [Empowering Education with Generative Artificial Intelligence Tools: Approach with an Instructional Design Matrix] / L. I. Ruiz-Rojas, P. Acosta-Vargas, J. De-Moreta-Llovet, M. Gonzalez-Rodriguez // Sustainability. - 2023. - Vol. 15, iss. 15. - Art. 11524 -р [in Kazakh]
Review
For citations:
Ospanova N., Tokzhigitova N., Baizhumanov S., Kuanysheva R. TECHNOLOGICAL CHALLENGES IN DEVELOPING A PLATFORM FOR MASSIVE OPEN ONLINE COURSES. Bulletin of the Khalel Dosmukhamedov Atyrau University. 2026;80(1):142-155. (In Kazakh) https://doi.org/10.47649/vau.26.v80.i1.12
JATS XML






