Against the backdrop of digital transformation in higher education, engineering education faces critical challenges including the theory-practice divide and high barriers to technical tool adoption. This study develops a tripartite framework (functional deconstruction – process modeling – data governance) for educational agent systems, which is built upon the “Coze platform” and rigorously aligned with the standards of China’s Emerging Engineering Education (3E) initiative for deployment in metaverse learning environments. By implementing multimodal interaction and adaptive decision-making mechanisms via three agent roles (teaching assistant/learning companion/management agent), we construct an immersive learning ecosystem and establish a context-aware paradigm for intelligent interactive education tailored to Chinese engineering education contexts. This research pioneers an innovative approach to cultivating engineering talent for the AI era through transformative learning methodologies.
References
[1] Zhang, C., Polette, A., Pinquié, R., Iida, M., De Charnace, H., Pernot, J. P. (2025) Reinforcement learning-based parametric CAD models reconstruction from 2D orthographic drawings. Computer-Aided Design, 103925.
[2] Xing, L., Li, Z., Wang, L. (2025) P‐4.9: applications and future trends of agents in the metaverse. SID Symposium Digest of Technical Papers, 56, 951-954.
[3] Tang, X., Jiang, L., Liu, G., Li, H. (2025) The interaction effect of pedagogical agent and emotional feedback on effective learning: a 2×2 factorial experiment in online formative assessment. Frontiers in Psychology, 16, 1610550.
[4] Wang, Y., Zhong, W., Huang, Y., Shi, E., Yang, M., Chen, J., Zheng, Z. (2025) Agents in software engineering: survey, landscape, and vision. Automated Software Engineering, 32(2), 70.
[5] Sadek, M., Calvo, R. A., Mougenot, C. (2025) The value-sensitive conversational agent co-design framework. International Journal of Human-Computer Interaction, 41(15), 9533-9564.
[6] Hu, L., Wu, Q., Qi, R. (2025) Empowering smart app development with SolidGPT: an edge-cloud hybrid AI agent framework. Advances in Engineering Innovation, 16(7), 86-92.
[7] Pan, Y., Zhang, J., Yu, J., Pan, Z. (2025) Modeling primary school students’ behavioral intention to use GenAI-augmented pedagogical agents: a hybrid SEM-ANN method. Education and Information Technologies, 1-20.
[8] Hu, W., Gong, R., Wu, S., Li, Y. (2025) A conversational agent based on contingent teaching model to support collaborative learning activities: impacts on students’ learning performance, self-efficacy and perceptions. Educational Technology Research and Development, 1-32.
[9] Güitta-López, L., Güitta-López, L., Boal, J., López-López, Á. J. (2025) Sim-to-real transfer via a style-identified cycle consistent generative adversarial network: zero-shot deployment on robotic manipulators through visual domain adaptation. Engineering Applications of Artificial Intelligence, 159, 111510.
[10] Schell, J., Ford, K., Markman, A. B. (2025) Building responsible AI chatbot platforms in higher education: an evidence-based framework from design to implementation. Frontiers in Education, 10, 1604934.
Share and Cite
Xie, T. (2025) Development and Empirical Study of a Multimodal Educational Agent System in Metaverse for Engineering Education Digital Transformation. Global Education Bulletin, 2(4), 31-39.