GenAI-Enabled Project-Based English Teaching Design for Intangible Cultural Heritage in Higher Vocational Education: A Case Study of Chinese Paper-Cutting

Abstract

Against the backdrop of globalization and China’s “vocational education going global” strategy, English instruction in higher vocational education must balance the development of practical language competence with the mission of promoting Chinese culture internationally. However, traditional instructional models have proven insufficient in meeting these dual objectives. This study takes Chinese paper-cutting, a representative form of intangible cultural heritage (ICH), as its thematic focus and explores the integration of Generative Artificial Intelligence (GenAI) with Project-Based Learning (PBL) in higher vocational English instruction. It proposes a practice-oriented instructional design framework centered on the goal of “telling the story of Chinese paper-cutting well in English.” The study targets first-year non-English majors in higher vocational institutions. Drawing on domestic large language models such as DeepSeek, Doubao, and KIMI, the research develops a comprehensive teaching design encompassing: (1) instructional objectives across four dimensions—knowledge acquisition, skill development, collaborative communication, and learning competence; (2) project scenario design, including a simulated interview transcript with master paper-cutting artist Shen Songbai, planning experiential activities for international visitors, and producing English short videos; (3) AI-supported project implementation, covering information retrieval, terminology translation, and script generation; and (4) multimodal presentation and assessment, incorporating automated formative evaluation and human–AI collaborative feedback mechanisms. The findings suggest that GenAI effectively alleviates teachers’ workload in scenario creation, task design, and process evaluation, while providing students with personalized and cross-cultural language learning support. The integration significantly enhances students’ comprehensive English proficiency, awareness of ICH dissemination, and teamwork competencies, thereby achieving an organic integration of the instrumental function of language learning and its broader cultural-educational role in vocational English education. Nevertheless, the study also identifies several limitations, including insufficient comparative analysis of output quality across different GenAI models and limited depth in cultural interpretation. Future research may explore multimodal GenAI integration, expand empirical sample sizes, and further refine human–AI collaborative assessment systems to provide more robust pedagogical guidance for ICH-oriented vocational English instruction in the intelligent era.