Title: Digital Transformation of Foreign Language Education: Elements, Challenges, and Pathways
Authors: Xiaoquan Pan, Huijuan Shao
Volume: 10
Issue: 5
Pages: 238-244
Publication Date: 2026/05/28
Abstract:
In the era of artificial intelligence, the digital transformation of foreign language education constitutes, in essence, a systematic restructuring of teaching objectives, processes, resources, and ecosystems, driven by data and underpinned by intelligent technology. Its core manifestations involve a triple transformation: human-machine collaborative teaching agents, multi-modal physical-virtual integrated resource platforms, and the dynamic competency mapping assessment paradigm. This research reveals significant structural contradictions confronting the transformation: compatibility challenges between technological applications and the highly interactive nature of foreign language learning, equity crises arising from digital literacy disparities, the cognitive dissolution of language learning objectives by generative artificial intelligence, and a theoretical void regarding the digital adaptation of its inherent humanistic attributes. This study posits that resolving these challenges necessitates multi-dimensional collaboration. Proposed pathways include: constructing a data-driven Intelligent Resource Analysis System (IRAS) and an Embedded Assessment Framework (EAF); developing integrated physical-virtual intelligent spaces to bridge teaching and research synergies; establishing a tiered system for advancing teacher digital literacy; and designing a closed-loop governance mechanism based on "data collection-diagnosis-intervention-iteration". This study proposes both a theoretical reference and practical paradigms for building a resilient digital ecosystem for foreign language education