With the proliferation of mobile smart terminals and the maturation of augmented reality (AR) technology, the field of education has been undergoing a transformation toward immersive and contextualized learning. In contrast, conventional English instruction remains constrained by static textbooks and abstract explanations, which have proven inadequate for constructing authentic language application scenarios. To address this gap, mobile AR-based English contextual teaching has emerged as a promising solution by converting linguistic knowledge into perceptible virtual contexts through the integration of real and virtual techniques. Despite its potential, existing studies reveal significant limitations. A number of investigations have focused solely on resource development without a comprehensive system architecture, while others have incorporated interaction analysis but lacked a foundation in cognitive theory. Moreover, assessment methods have primarily relied on simplistic feedback mechanisms, with limited incorporation of dynamic data tracking. To overcome these challenges, a mobile AR-based English contextual teaching system was designed, accompanied by an in-depth cognitive analysis of group interactive behavior. A hybrid context generation framework was constructed, functional modules for a mobile application were developed, and the mechanisms through which group interaction influences language cognition were examined. This study provides a systematic approach for the deep integration of technology and English education and offers a theoretical basis for optimizing contextual teaching strategies.
Fengfen Gao (Wed,) studied this question.