Integration of Coze AI Multi-Agent Virtual Assistant into Moodle LMS: Technical Architecture Analysis and Teaching Performance Evaluation
DOI:
https://doi.org/10.51453/3093-3706/2026/1481Abstract
In the context of higher education digital transformation, the application of large language models (LLMs) and Multi-Agent Systems (MAS) is an inevitable trend. This study presents the architecture and empirical evaluation of the successful integration of the Coze AI Virtual Assistant into the Moodle Learning Management System (LMS) at Viet Tri University of Industry (VUI). We focus on designing the Coze Bot with specialized "Skills" (Tools) operating as AI agents to support faculty in three key aspects: (1) Assisting in course content design and development; (2) Automating student frequently asked questions (FAQ) through querying a dedicated Knowledge Base; and (3) Providing summarized analysis of learning activities. The technical architecture employs an API/Chat SDK to embed the domain-specific LLM into the LMS user interface. Empirical results indicate that the solution reduced the time spent by faculty on answering recurring FAQ by 73% (p < 0.01, validated by paired-sample ttest), while enhancing timely 24/7 interaction. This demonstrates the potential of integrating domain-specific knowledge via Retrieval-Augmented Generation (RAG) within a Multi-Agent architecture to significantly improve work efficiency and teaching quality in higher education. Keywords: AI Coze, Virtual Assistant, Moodle LMS, Multi-Agent Architecture, Knowledge Base, Teaching Performance, API Integration.
Downloads
References
1. M. H. H. L. Lee et al., “Intelligent tutoring systems for science education: A review of recent developments,” Journal of Science Education and Technology, vol. 28, no. 6, pp. 614-633, 2019.
2. X. Zhai and R. H. Nehm, “Examining generative artificial intelligence (GenAI) in assessing students' responses to socio-scientific issues in physics,” Taylor & Francis Online, 2023.
3. Y. D. Patarakin and K. D. Salimullin, “Design and empirical study of a multi-agent learning assistant for enhanced student engagement and mastery on the Coze Platform,” in Proc. 2025 International Conference on Intelligent Systems and Learning Technologies (ISLT), 2025.
4. ResearchGate, “Application of Artificial Intelligence for Virtual Teaching Assistance, Case study: Introduction to Information Technology,” 2023. [Online]. Available: ResearchGate. Accessed: November 14, 2025.
5. Q. K. Nguyen, “Research on the development and deployment of a Moodle-based learning management system (LMS) contributing to educational digital transformation,” Dong Do Science and Technology Journal, Dong Do University, 2025.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
All articles published in SJTTU are licensed under a Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA) license. This means anyone is free to copy, transform, or redistribute articles for any lawful purpose in any medium, provided they give appropriate attribution to the original author(s) and SJTTU, link to the license, indicate if changes were made, and redistribute any derivative work under the same license.
Copyright on articles is retained by the respective author(s), without restrictions. A non-exclusive license is granted to SJTTU to publish the article and identify itself as its original publisher, along with the commercial right to include the article in a hardcopy issue for sale to libraries and individuals.
Although the conditions of the CC BY-SA license don't apply to authors (as the copyright holder of your article, you have no restrictions on your rights), by submitting to SJTTU, authors recognize the rights of readers, and must grant any third party the right to use their article to the extent provided by the license.
