自助旅行華語教材設計研究-以 A2及 B1學習者為對象

Abstract

隨著 COVID-19 疫情趨緩，來臺自由行旅客逐年回升，然而語言障礙仍為外籍旅客進行自助旅行時面臨的主要挑戰。鑑於此，本研究依據國家教育研究院「觀光能力指標」，針對 A2 與 B1 級華語學習者進行需求分析，設計《臺灣走透透》旅遊華語教材，並進行教材評鑑。本研究採設計研究法，以文獻分析與問卷調查法了解教材編寫原則與學習者需求。問卷結果顯示，未曾來臺者普遍認為華語能力對於自助旅行具高度實用性，曾來臺者亦認同語言能力有助於提升整體旅遊體驗。兩組皆高度重視購物、餐飲、文化理解與旅遊應變等情境，而景點偏好則集中於墾丁、淡水、故宮、迪化街等兼具自然與文化特色的場域。根據需求分析結果，教材採紙本與數位雙版本整合設計，整合 ChatGPT 、生詞卡、實地影片等多模態資源。專家評鑑肯定教材在內容規劃與數位設計上的整體架構，並建議未來可強化難度分級與 AI 對話靈活性；外籍學習者則正向回饋教材實用性與內容豐富度，並提出改善語音自然度與版面閱讀性等建議。總體而言，旅遊華語教材應兼顧語言功能與文化深度，並依學習者語言程度調整任務難度與互動設計。未來可持續優化多語版本整合、學習資源模組化與 AI 輔助應用，以更全面回應多元學習者之語言學習需求與跨文化溝通挑戰。As post-pandemic tourism recovers, independent travel to Taiwan has steadily increased. However, language barriers remain a key challenge for foreign visitors. In response, this study developed and evaluated a travel Chinese textbook, Traveling Through Taiwan, based on the “Tourism Competency Indicators” from Taiwan’s National Academy for Educational Research, with a focus on A2 and B1 learners. Adopting a design-based research approach, the study incorporated literature review and questionnaire surveys (n=95) to explore learners’ backgrounds, language needs, and topic preferences. Results show that learners without Taiwan experience consider Chinese proficiency highly useful for travel, while experienced learners also value its benefits, though with slightly lower motivation. Both groups prioritized scenarios related to shopping, dining, cultural understanding, and emergencies. Popular destinations included Kenting, Tamsui, the National Palace Museum, and Dihua Street. The textbook features both print and digital formats, integrating multimodal tools such as ChatGPT dialogues, vocabulary flashcards, and real-world videos. Expert evaluations affirmed the structure and content, recommending clearer level differentiation and enhanced AI interactivity. Learner feedback highlighted the material’s practicality and cultural richness, along with suggestions for improving audio quality and layout design. Overall, the study suggests that travel Chinese materials should balance language utility and cultural depth, with level-appropriate tasks and interactive support. Future improvements may focus on modular design, multilingual resources, and more flexible AI integration to meet diverse learner needs.