Strategies for Enhancing Linguistic Teaching Effectiveness Based on Interactive Technologies in Mobile Learning Environments

Abstract

The digital transformation of education and the widespread adoption of mobile devices have propelled mobile learning to become the core setting for linguistic teaching, with extensive applications in fields such as second language acquisition and intercultural communication. However, current practices reveal issues such as a disconnect between interactive technology applications and the intrinsic laws of language acquisition, as well as imbalanced cognitive load for learners, which severely hinder the improvement of teaching quality. This study is grounded in the input hypothesis and interaction hypothesis of applied linguistics, the theory of ubiquitous mobile learning in educational technology, and cognitive load theory in cognitive psychology. By using a mixed research method that combines surveys, classroom observations, and quasi-experimental research, the study systematically analyzes the current application of interactive technologies in mobile linguistic teaching, identifies key pain points, and constructs a “technology-teaching-cognition” three-dimensional collaborative strategy system to enhance teaching effectiveness. The empirical findings show that targeted interactive technology designs, such as AR-based situational interaction, AI-driven feedback, and cross-cultural collaborative interaction, can effectively improve the comprehensibility of input, the depth of knowledge internalization, and the authenticity of language output in mobile linguistic teaching. This research provides a reliable reference model for the theoretical refinement and practical optimization of global digital linguistic education.