隨著生成式 AI（Generative AI）逐漸應用於語言學習，本研究旨在結合 IDEA 框架進行指令設計，並發展與實施融合 ChatGPT-based 教學系統「拒絕小老師（Refusal Buddy）」的情境化華語拒絕策略教學模式，從學習成效、學習者感知與學習挑戰三個面向，探討其對語用能力發展的影響及運作機制。
本研究採設計型研究（Design-Based Research, DBR）取向，研究對象為18位國籍多元、華語程度介於CEFR B1至C1之學習者。並透過前後測資料、學習語料分析、回饋問卷與訪談資料進行混合分析。
研究結果顯示，生成式 AI 輔助教學有助於提升學習者之語用適切度與策略完整度，學習者的拒絕表現亦由單一策略與一次性輸出，逐漸發展為具多策略組合與話輪結構之互動模式。相較之下，語氣自然度僅小幅提升，語言準確度的進步則相對有限。在學習感知方面，多數學習者對 AI 輔助語用學習持正向態度，認為其有助於提升語用覺察、語氣調整與策略運用能力，並提供具互動性、即時性與低焦慮之練習環境。然而，研究亦發現 AI 回饋存在情境控制不穩定、回饋品質不一致與表達公式化等限制。
本研究據此提出生成式 AI 融入華語語用教學的六項設計原則，並將教學歷程區分為四個主要階段，以作為未來華語語用教學與 AI 融入設計之參考。

With the growing use of generative artificial intelligence (AI) in language learning, this study aims to develop and implement a contextualized instructional model for teaching Chinese refusal strategies through prompt design informed by the IDEA framework and a ChatGPT-based instructional system, Refusal Buddy. It examines its effects on pragmatic development and underlying mechanisms from three perspectives: learning outcomes, learner perceptions, and learning challenges.
Adopting a Design-Based Research (DBR) approach, this study involved 18 Chinese language learners from diverse national backgrounds, with proficiency levels ranging from CEFR B1 to C1. A mixed-methods design was employed, incorporating pre- and post-tests, discourse analysis, questionnaires, and interviews.
The results indicate that AI-assisted instruction significantly enhances learners’ pragmatic competence. Notable improvements were found in pragmatic appropriateness and strategy completeness, as learners progressed from single-strategy, one-shot responses to structured multi-strategy combinations distributed across two turns. Moderate gains were observed in naturalness of tone, while improvements in linguistic accuracy were limited. In terms of learner perceptions, most participants reported positive attitudes toward AI-supported learning, highlighting its effectiveness in enhancing pragmatic awareness, tone adjustment, and strategy use, as well as reducing anxiety and providing interactive, convenient, and immediate practice. However, issues such as inconsistent feedback quality, deviations in scenario control, and overly formulaic suggestions were identified.
Based on these findings, this study proposes six design principles for integrating generative AI into Chinese pragmatic instruction and further conceptualizes the instructional process into four major stages, providing pedagogical implications for future Chinese pragmatic teaching and AI-integrated instructional design.

中文文獻
王愛華（2001）。英漢拒絕言語行為表達模式調查。外語教學與研究，33(3)，178–185。
王楚蓁、韋志安（2024）。ChatGPT輔助專業華語教材編寫——以單班課師生協作模式為例。臺大華語文學習與科技，3，71–98。
方淑華（2018）。臺籍母語者與日、美籍學習者華語拒絕語用研究及教學建議（博士論文）。國立臺灣師範大學。
白明弘（2023）。學習語言的良師益友－ChatGPT在華語學習上的應用簡介。華文世界，132，157–173。
曲禹宣（2012）。現代漢語拒絕言語行為與策略及其教學探究（碩士論文）。國立政治大學。
伍宥蓁（2022）。華語與韓語拒絕策略之對比分析——以職場溝通為例（碩士論文）。國立臺灣師範大學。
何自然（1996）。語用學概論。湖南教育出版社。
何自然、冉永平（2009）。新編語用學概論。北京大學出版社。
何良慶（2016）。跨文化溝通教材設計研究：以拒絕和請求言語行為為主題（碩士論文）。國立臺灣師範大學。
李婉妤（2006）。跨文化華語拒絕策略研究：以美加籍學生為例（碩士論文）。國立高雄師範大學。
谷慧娟（2007）。漢英拒絕策略的文化映射。華東理工大學學報（社會科學版），22(3)，110–114。
林宛蓉（2024）。生成式AI應用於易混淆詞之教學設計〔論文發表〕。第23屆台灣華語文教學年會暨國際學術研討會，國立暨南國際大學，南投。
林翠雲（2024）。AI工具應用之華語師資培訓課程設計。國立臺灣科技大學人文社會學報，18(3)，183–213。
許力生（2006）。跨語言研究的跨文化視野。上海外語教育出版社。
許惠美（2024）。生成式 AI 與教育：倍力與解放？臺灣教育評論月刊，13(11)，55–60。
胡瑞雪（2015）。法籍華語學習者與臺籍華語母語者拒絕策略之對比分析。中原華語文學報，16，31–80。
姚俊（2003）。從英漢拒絕策略的語用對比看中西文化差異。山東外語教學，（1），12–17。
舒兆民（2002）。網路華語語體及文化課程教學設計（碩士論文）。國立臺灣師範大學。
舒兆民（2004）。華語抱怨言語行為分析及其教學建議。2004台灣華語文教學研討會論文集。佛光大學。
舒兆民（2007）。計量分析英日語人士華語學習者之拒絕中介語。華語文教學研究，4(1)，99–124。
馬月蘭（1998）。中美拒絕言語行為比較研究。青海師範大學學報，（4），81–87。
張絮茵（2012）。商務漢語拒絕言語行為研究。華語文教學研究，9(1)，73–98。https://doi.org/10.6393/JCLT.201203.0074
張群（2024）。透過 AI 科技和 YouTube 平台輔助提升華語師資培育生之教學和學習成效：問題導向學習模式在華語教材設計中的應用。國立臺中科技大學。
陳梅影（2016）。臺灣學生與馬來西亞僑生於請求與拒絕行為之道歉語分析。臺灣華語教學研究，（12），27–42。
陳梅影、曾嘉悌（2015）。臺灣大學生的請求策略與當代華語教材請求語義公式之比較。華語文教學研究，12(3)，125–151。https://doi.org/10.6393/JCLT.201509_12(3).0005
陶氏美玲（2025）。華語與越語拒絕策略之對比研究與華語教學建議（碩士論文）。國立臺灣師範大學。
彭喬渝（2019）。華語回應拒絕之語用策略分析及其教學應用（碩士論文）。國立臺灣師範大學。
賴紋萱（2012）。拒絕行為之難點分析及教學應用（碩士論文）。國立臺灣師範大學。
蔡薇（2023）。ChatGPT環境下的漢語學習與教學。語言教學與研究，（4），13–23。
劉珣（2005）。對外漢語教育學引論。北京語言大學出版社。
謝佳玲（2010）。華語拒絕請求的策略分析。臺灣華語教學研究，（1），111–137。
謝佳玲、賴紋萱（2010）。華語拒絕策略與清淨因素之互動。第四屆美國國際教育交流協會華語文教學研討會論文集（1–26）。國立政治大學。
英文文獻
Algobaei, F., & Alzain, E. (2026). Prompt engineering for non-native English learners: A generative AI approach to personalised language feedback. Social Sciences & Humanities Open, 13, 102341. https://doi.org/10.1016/j.ssaho.2025.102341
Amatriain, X. (2024). Prompt design and engineering: Introduction and advanced methods. arXiv preprint arXiv:2401.14423. https://doi.org/10.48550/arXiv.2401.14423
Austin, J. L. (1962). How to do things with words. Clarendon Press.
Bastani, H., Bastani, O., Sungu, A., Ge, H., Kabakcı, Ö., & Mariman, R. (2024). Generative AI can harm learning. The Wharton School Research Paper. http://dx.doi.org/10.2139/ssrn.4895486
Beebe, L. M., Takahashi, T., & Uliss-Weltz, R. (1990). Pragmatic transfer in ESL refusals. In R. C. Scarcella, E. S. Andersen, & S. D. Krashen (Eds.), Developing communicative competence in a second language (pp. 55–73). Newbury House.
Blum-Kulka, S., House, J., & Kasper, G. (Eds.). (1989). Cross-cultural pragmatics: Requests and apologies. Ablex.
Branch, R. M. (2009). Instructional design: The ADDIE approach. Springer.
Brown, P., & Levinson, S. C. (1987). Politeness: Some universals in language usage. Cambridge University Press.
Butler-Pascoe, M. E. (2011). The history of CALL: The intertwining paths of technology and second/foreign language teaching. International Journal of Computer-Assisted Language Learning and Teaching, 1(1), 16–32.
Celik, I., Dindar, M., Muukkonen, H., & Järvelä, S. (2022). The promises and challenges of artificial intelligence for teachers: A systematic review of research. TechTrends, 66(4), 616–630. https://doi.org/10.1007/s11528-022-00715-y
Chang, E. Y. (2023). Prompting large language models with the Socratic method. 2023 IEEE 13th Annual Computing and Communication Workshop and Conference (CCWC) (pp. 351–360). https://doi.org/10.1109/CCWC57344.2023.10099179
Chen, X., Ye, L., & Zhang, Y. (1995). Refusing in Chinese. In G. Kasper (Ed.), Pragmatics of Chinese as native and target language (pp. 119–163). University of Hawaii Press.
Chung, S. H. A. (2007). Refusal strategies used by Chinese and American college students. NKNU Journal of Humanities and Arts, 23, 85–107.
Cohen, A. D. (1996). Investigating the production of speech act sets. In S. M. Gass & J. Neu (Eds.), Speech acts across cultures: Challenges to communication in a second language (pp. 21–43). Mouton de Gruyter.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
Eager, B., & Brunton, R. (2023). Prompting higher education towards AI-augmented teaching and learning practice. Journal of University Teaching and Learning Practice, 20(5), 1–19. https://doi.org/10.53761/1.20.5.02
Ekin, S. (2023). Prompt engineering for ChatGPT: A quick guide to techniques, tips, and best practices. TechRxiv. https://doi.org/10.36227/techrxiv.22683919
El-Dakhs, D. A. S. (2020). The art of saying “no” to university students: A pragmatic analysis of the speech act of refusal in teacher-student role-plays. Journal of Language and Education, 6(4), 55–67.
Farrokhnia, M., Banihashem, S. K., Noroozi, O., & Wals, A. (2023). A SWOT analysis of ChatGPT: Implications for educational practice and research. Innovations in Education and Teaching International, 61(3), 460–474. https://doi.org/10.1080/14703297.2023.2195846
Federiakin, D., Molerov, D., Zlatkin-Troitschanskaia, O., & Maur, A. (2024). Prompt engineering as a new 21st century skill. Frontiers in Education, 9, 1366434.
Gao, X., & Deng, L. (2025). Rating scales in L2 speech act research: A systematic review. Research Methods in Applied Linguistics, 4(2), Article 100204.
Garg, A., Soodhani, K. N., & Rajendran, R. (2025). Enhancing data analysis and programming skills through structured prompt training: The impact of generative AI in engineering education. Computers and Education: Artificial Intelligence, 8, 100380.
Godwin-Jones, R. (2024). Generative AI, pragmatics, and authenticity in second language learning. Language Learning & Technology, 28(1), 1–11.
Goffman, E. (1967). Interaction ritual: Essays on face-to-face behavior. Anchor Books.
González-Lloret, M. (2016). A practical guide to integrating technology into task-based language teaching. Georgetown University Press.
Google. (2024). Generative AI for educators. https://skillshop.exceedlms.com/student/path/1176018
Guo, Y. (2012). Chinese and American refusal strategy: A cross-cultural approach. Theory and Practice in Language Studies, 2(2), 247–256.
Haristiani, N. (2019). Artificial intelligence (AI) chatbot as language learning medium: An inquiry. Journal of Physics: Conference Series, 1387, 012020. https://doi.org/10.1088/1742-6596/1387/1/012020
Hong, W. (2011). Refusals in Chinese: How do L1 and L2 differ? Foreign Language Annals, 44(1), 122–142. https://doi.org/10.1111/j.1944-9720.2010.01107.x
Hu, J., Floyd, S., Jouravlev, O., Fedorenko, E., & Gibson, E. (2023). A fine-grained comparison of pragmatic language understanding in humans and language models. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (pp. 4194–4213). Association for Computational Linguistics.
Huang, W., Hew, K. F., & Fryer, L. K. (2022). Chatbots for language learning—Are they really useful? A systematic review of chatbot-supported language learning. Journal of Computer Assisted Learning, 38(1), 237–257. https://doi.org/10.1111/jcal.12610
Hwang, G.-J., & Chen, N.-S. (2023). Exploring the potential of generative artificial intelligence in education: Applications, challenges, and future research directions. Educational Technology & Society, 26(2). https://doi.org/10.30191/ETS.202304_26(2).0014
Hwang, M., Lee, K.-H., & Lee, H.-K. (2025). A word to the wise: Crafting impactful prompts for ChatGPT. System, 133, 103756.
Kasper, G. (1990). Linguistic politeness: Current research issues. Journal of Pragmatics, 14(2), 193–218.
Kasper, G., & Rose, K. R. (2002). Pragmatic development in a second language. Blackwell.
Knoth, N., Tolzin, A., Janson, A., & Leimeister, J. M. (2024). AI literacy and its implications for prompt engineering strategies. Computers and Education: Artificial Intelligence, 6, 100225.
Krashen, S. D. (1982). Principles and practice in second language acquisition. Pergamon Press.
Lee, B. J., & Cook, D. R. (2024). Exploring the potential of AI for pragmatics instruction. Technology in Language Teaching & Learning, 6(3). https://doi.org/10.29140/tltl.v6n3.1521
Lee, H.-Y. (2011). Linguistic politeness in the Chinese language and culture. Theory and Practice in Language Studies, 1(1), 1–9.
Leech, G. N. (1983). Principles of pragmatics. Longman.
Li, S. (2014). The effects of different levels of linguistic proficiency on the development of L2 Chinese request production during study abroad. System, 45, 103–116.
Li, S., Wen, T., Li, X., Feng, Y., & Lin, C. (2023). Comparing holistic and analytic marking methods in assessing speech act production in L2 Chinese. Language Testing, 40(2), 249–275.
Lin-Zucker, M., Bellassen, J., & Zucker, J.-D. (2025). Prompting ChatGPT for Chinese learning as L2: A CEFR and EBCL level study. arXiv. https://doi.org/10.48550/arXiv.2501.15247
Liu, J., & Xie, L. (2014). Examining rater effects in a WDCT pragmatics test. Iranian Journal of Language Testing, 4(1), 50–66.
Lo, L. S. (2023). The art and science of prompt engineering: A new literacy in the information age. Internet Reference Services Quarterly, 27(4), 203–210.
Long, Y., Luo, H., & Zhang, Y. (2024). Evaluating large language models in analysing classroom dialogue. npj Science of Learning, 9, Article 60. https://doi.org/10.1038/s41539-024-00260-0
Park, J., & Choo, S. (2024). Generative AI prompt engineering for educators: Practical strategies. Journal of Special Education Technology.
Pomerantz, A. (1984). Agreeing and disagreeing with assessments. In J. M. Atkinson & J. Heritage (Eds.), Structures of social action (pp. 57–101). Cambridge University Press.
Prasetya, R. E., & Syarif, A. (2023). ChatGPT as a tool for language development: Investigating its impact on proficiency and self-evaluation accuracy in Indonesian higher education. VELES Voices of English Language Education Society, 7(3), 402–415.
Qian, Y. (2025). Prompt engineering in education: A systematic review of approaches and educational applications. Journal of Educational Computing Research, 63(7–8), 1782–1818.
Rahim, R., Purwanti, I. T., & Daud, A. (2026). The development of animated videos for teaching refusal speech act. Journal of Culture, English Language Teaching, Literature and Linguistics, 13(1), 21–36.
Sacks, H., Schegloff, E. A., & Jefferson, G. (1974). Turn-taking systematics. Language, 50(4), 696–735.
Searle, J. R. (1969). Speech acts: An essay in the philosophy of language. Cambridge University Press.
Searle, J. R. (1976). A taxonomy of illocutionary acts. Language in Society, 5(1), 1–23. https://doi.org/10.1017/S0047404500006837
Smaldino, S. E., Lowther, D. L., Mims, C., & Russell, J. D. (2019). Instructional technology and media for learning (12th ed.). Pearson.
Taguchi, N. (2011). Teaching pragmatics: Trends and issues. Annual Review of Applied Linguistics, 31, 289–310. https://doi.org/10.1017/S0267190511000018
Tang, X. (2019). Task modality and pragmatic development. System, 80, 48–59.
Tang, X., & Taguchi, N. (2020). Designing and using a scenario-based digital game to teach Chinese formulaic expressions. CALICO Journal, 37(1), 1–22.
Thomas, J. (1983). Cross-cultural pragmatic failure. Applied Linguistics, 4(2), 91–112.
Velásquez-Henao, J. D., Franco-Cardona, C. J., & Cadavid-Higuita, L. (2023). Prompt engineering: A methodology for optimizing interactions with AI-language models in the field of engineering. DYNA, 2023(230), 9–17. https://doi.org/10.15446/dyna.v90n230.111700
Wallace, R. S. (2009). The anatomy of A.L.I.C.E. In R. Epstein, G. Roberts, & G. Beber (Eds.), Parsing the turing test: Philosophical and methodological issues in the quest for the thinking computer (pp. 181–210). Springer.
Wolfson, N. (1986). The bulge: A theory of speech behavior and social distance. Working Papers in Educational Linguistics, 2(1). https://repository.upenn.edu/wpel/vol2/iss1/3
Wolfson, N. (1988). The bulge: A theory of speech behavior and social distance. In J. Fine (Ed.), Second language discourse: A textbook of current research (pp. 21–38). Ablex.
Wood, L. A., & Kroger, R. O. (1994). The analysis of face work in discourse. Journal of Pragmatics, 21(3), 239–260.
Woo, D. J., Guo, K., & Susanto, H. (2024). Exploring EFL students’ prompt engineering in human-AI story writing: An activity theory perspective. Interactive Learning Environments, 1–20. https://doi.org/10.1080/10494820.2024.2361381
Xu, S., Qin, L., Chen, T., Zha, Z., Qiu, B., & Wang, W. (2024). Large language model based situational dialogues for second language learning. arXiv. https://doi.org/10.48550/arXiv.2403.20005
Zhang, F. (2022). A developmental study of pragmatic strategies of refusals by Chinese English majors. English Language Teaching, 15(10), 1–1.
Zhao, C. (2021). Explicit speech act instruction for developing EFL students’ pragmatic competence. International Journal of English Language Teaching, 9(4), 26–35.
Zhou, Y., Muresanu, A. I., Han, Z., Paster, K., Pitis, S., Chan, H., & Ba, J. (2023). Large language models are human-level prompt engineers [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2211.01910