Construction of the digital intelligence-enabled intervention model for learning engagement

Academic English writing is a crucial component of undergraduate English education. However, undergraduates commonly face challenges such as unclear topic selection, imprecise language expression, and a lack of depth and logical coherence in analysis and argumentation. This study, grounded in AGIL theory (Adaption, Goal Attainment, Integration, Latency Pattern Maintenance), integrates generative artificial intelligence with instant feedback to develop a “Human-Computer Dual-Instructor” model for learning engagement intervention. The model consists of four subsystems: the objective system, the environmental system, the operational system, and the response system for learning engagement intervention. Through an iterative intervention response mechanism, this model is capable of dynamically assessing intervention effects and ensuring the orderly flow of data among the subsystems. Using an academic English writing course as an example, this model is applied to the design of teaching interventions, aiming to enhance students’ learning engagement and academic writing skills.