Research on Closed Loop Management Information System of Hybrid Teaching Driven by Generative Artificial Intelligence

Abstract

To address significant problems such as feedback lag, insufficient personalization and static teaching resources in hybrid teaching, this paper proposes a closed-loop adaptive generative teaching engine—CLAGTE—driven by generative artificial intelligence. The engine consists of multi-modal student state awareness network MHAFNet, time-series attention knowledge tracking model TAKT, teaching strategy decision module based on near-end strategy optimization and retrieval enhancement generative content creation module, which form a full-link closed loop of “perception-diagnosis decision-generation”. Experimental results on three public datasets of ASSISTments, Junyi Academy and EdNet show that the AUC of CLAGTE in
performance comparison is as high as 0.879, which is about 2.6 percentage points higher than the optimal baseline DIMKT. Its AUC decreases by only 11.9% under 30% label noise, and its robustness is significantly better than that of the comparative model. At the same time, the comprehensive mean of practical subjective score reaches 4.33, and the interpretable Spearman correlation coefficient is 0.68. The accuracy rate of learning gain simulation increases by 7.8% after a single intervention, and the cumulative accuracy rate increases by 14.6%. In addition, its cross-domain zero sample migration AUC remains above 0.75. Furthermore, the ablation experiment verifies the effectiveness of each module. In summary, CLAGTE achieves the intelligent closed loop of hybrid teaching management through the collaboration of multi-modal fusion, dynamic knowledge tracking, reinforcement learning adaptive strategy and generative content supply, and provides a feasible technical solution for personalized education.

Keywords: Generative artificial intelligence; hybrid teaching; closed-loop management information system; knowledge tracking; multimodal fusion

Cite As

J. Zhang, X. Wang, "Research on Closed Loop Management Information System of Hybrid Teaching Driven by Generative Artificial Intelligence", Engineering Intelligent Systems, vol. 35 no. 5, pp. 653-664, 2026.