From Static to Dynamic: Constructing AIGC-Empowered Resource Ecosystem for Ideological Education in EFL Audio-Visual-Oral Courses — An Empirical Study of the Three-Dimensional Five-Loop Model

Against the backdrop of China Education Modernization 2035 and the Guide-lines for Curriculum Ideology and Political Education in Higher Edu-cation, this study addresses the challenges of inefficient ideological content supply, simplis-tic evaluation systems, and superficial technology use in English au-dio-visual-oral courses. Drawing on the Content-Language Inte-gration Learning (CLI) and Production-Oriented Approach (POA) theories, an AIGC-empowered "Three-Dimensional Five-Loop" model is constructed, integrating dynamic re-source generation (e.g., AI-adapted corpora on "poverty alleviation" with 300% higher update efficiency via GPT-4.0), con-textual task design and data-driven evaluation. A quasi-experiment involv-ing 280 experimental students and 70 controls reveals significant im-provements: Policy concept expression accuracy in English reached 82.7% (vs. 44.7% in controls), with cross-cultural case cita-tion frequency increas-ing by 130% (5.73 vs. 2.49 times/1,000 words). Active use of Chinese poli-cy cases in oral output rose to 65% (vs. 20%), and weekly platform en-gagement duration was tripled (36 vs. 12 minutes). Qualitative feedback showed 89% technology acceptance, with "cultural confidence" dis-course deepened by 3.5x in reflection logs. Challenges such as content homog-eni-zation (mitigated via "AI suggestion-manual revision" tasks) and teacher digital literacy gaps (addressed through prompt design training) are dis-cussed. The model transforms static textbooks materials into dynamic vis-ual and audio resources ecosystems, providing a replicable framework for integrating techno-logical innovation with ideological education in foreign language courses.