Faculty Publications and Conference Presentations

The rapid advancement of Generative Artificial Intelligence (AI) has ushered in both unprecedented opportunities and challenges within the realm of higher education, particularly in the context of English language teaching. This article delineates seven foundational principles that aim to optimize the integration of Generative AI in teaching and learning environments. Developed from the practical experiences of frontline language teachers at Hong Kong universities, these principles advocate for a paradigm shift in the perception and utilization of AI—from viewing it merely as a tool for information retrieval to recognizing it as a robust collaborator capable of enhancing cognitive development and interaction. These principles emphasize the importance of leveraging AI's capabilities to foster a more interactive and dynamic educational experience. They address the need to prioritize AI as a reasoning engine, ensure the quality of data inputs, customize AI interactions, actively harness AI to simulate human textual interactions, and focus on ethical AI usage, among others. By implementing these principles, educators can transform AI into a powerful ally that not only streamlines educational processes but also significantly enriches learning outcomes. This approach prepares students to adeptly navigate and analyze the complex information landscapes of their academic and professional futures, thus making AI an essential partner in education. The article serves as a call to action for educators to engage deeply with AI technologies, proposing a thoughtful framework that fosters enhanced educational practices and prepares students for a digitally integrated world.

<p>This study explores the transformative impact of participatory research on the conceptualization of Kongish. A hybridized written form comprising a creative blend of Cantonese and English, Kongish is a grassroots media-linguistic phenomenon within the vibrant sociocultural ecology of Hong Kong. Our research aims to evaluate how a participatory methodology—as opposed to traditional researcher-oriented approaches where researchers remain at arm's length with their research subjects—reshapes the understanding of Kongish as well as Hong Kong English (HKE). Using a participatory linguistics framework, this study triangulates data from focus group interviews, individual interviews, and online surveys to explore the reciprocal influences between researchers and participants. The study is organized into two tiers: first, the transformation of participants, and second, the transformation of researchers. Each tier draws on personal narratives to offer distinct insights into real-life encounters with Hong Kong's written vernacular. By integrating the “lived experiences” of both researchers and participants, the study reveals how our interactions continuously influence each other's perceptions of language, language practices, and personal identities.</p>

This article examines the transformative role of Artificial Intelligence (AI), Generative AI (GenAI), and Large Language Models (LLMs) like ChatGPT and DeepSeek in language teaching and learning. It highlights their capabilities, including personalized content generation, automated assessment, real-time feedback, and administrative efficiency, while emphasizing the necessity of prompt engineering to optimize outputs. The PROMPT (Persona, Requirements, Organization, Medium, Purpose, Tone) framework is introduced as a structured approach to crafting effective prompts. Case studies, such as DeepSeek’s Python code generation, demonstrate practical applications. However, the article critically addresses limitations like bias, factual inaccuracies, and ethical concerns, advocating for rigorous fact-checking and balanced human-AI collaboration. By synthesizing research and practical examples, this article underscores AI’s potential to enhance language education while urging educators to adopt critical literacy and ethical frameworks to mitigate risks and ensure equitable, human-centered learning experiences.

<p>This brief article explores the integration of Generative Artificial Intelligence (GenAI) tools into blended learning environments for designing and teaching pronunciation tasks. Adapting Calamlam’s (2016) conceptual framework, a flowchart is proposed to guide the use of three GenAI tool types to enhance pronunciation instruction: Listen-Mimic Type, Analyze-Feedback Type, and Practice-Feedback Type. The framework facilitates effective use of both synchronous and asynchronous learning opportu-nities. While this study offers a theoretical overview, it highlights the potential for broader application across various language skills. Future research is necessary to evaluate the effectiveness of these tools and their role in the evolving educational landscape.</p>

ここ数年の間に GenAI Technology の急速な進展は目覚ましい。ビジネ スのみならず、教育分野での GenAI Technology の活用が注目されている。 言語教育では、英語教育や中国語教育においては、実践事例、研究事例が 報告され始めている。世界的に見て大変に注目されている研究題目となっ ている。ところが、第３外国語教育、特に日本語教育での実践事例や研究 事例は限られている。正に、始まったばかりのようである。 本稿では、大学の初級日本語コースでの Chatbot の実践的活用について 報告する。日本語初級者においても、Chatbot は学習を少しでも効率よく できるツールとなるのか、初級者ではどのような学習内容に使うのか、 Chatbot 活用の良かった点や改善が必要と思われる点は具体的に何か、な どを学生の声をもとに明確にする目的で取り組んだ。 調査対象学生 40 名で、毎月ミニレポートという形で調査を学期中継続 した。Chatbot は対話的に学習者と関わることができる。これは学生には 親しみやすく興味が持てたようで Chatbot 活用には大変に積極的であった。 40 名全員からデータを回収することができた。学生が特に活用した学習 内容としては、１）語彙の学習、２）日本語の文法学習、３）日本文化に 関する学習が上位 3 つであった。 学生からは、Chatbot の対話型アプローチが楽しいという意見や、いつ でも使える、欲しい情報がすぐに手に入るなど良かった点が大変多く寄せ られた。一方、改善点としては説明が難しくわかりにくい、正確ではない ように感じる時があったなど、数は多くはなかったが寄せられた。 Chatbot の活用は初級日本語コースにおいて、教育的有用性が十分に認 められた。対話型学習、日本語の学習サポート、日本文化情報の提供など の点で、GenAI Technology の日本語教育への活用可能性を示唆している。 今後の日本語教育における GenAI Technology の一層の活用が期待される。

從「微軟小冰」出版詩集到生成式人工智能的崛起，人工智能參與詩歌創作的問題已有不少討論。然而，生成式AI的應用不僅侷限於創作層面，其還可以作為現代詩教學的輔助工具，為詩歌教育提供新的可能性。筆者近年任教坊間的一些現代詩寫作班時，曾嘗試引入生成式AI輔助教學。本文將結合個人教學經驗，淺談 生成式AI在現代詩教學中的應用潛力，並對其未來發展作出一些展望。

本研究以香港高校一门中文传意课程中粤语母语学生的普通话产出为材料，分析影响「言语可懂度（speech intelligibility）」（参 Smith &amp; Nelson, 1985；Munro &amp; Derwing, 1995）的语音要素。针对 19 位发音人 126 个可懂度低的音节，研究发现：（1）单一成分偏误中，韵母偏误占比最高，其次是声母偏误；（2）多种成分偏误组合中，「声母 +韵母」偏误占比最高；（3）声母偏误中，sh 误读最为多见；（4）韵母偏误中，i 误读最为多见，含介音韵母误读亦较多；（5）声调偏误中，第四声误读最为多见，与其他三声相混，二、三声也有相混情况。研究表明，在以传意为目标、面向粤语母语者的普通话教学中，可优先教学声韵母，声调教学稍列其后；重点及优先教学舌尖后音与舌面音（尤其是声母 sh 与 x）、声母 r、单韵母 i 与 u、以及含介音的音节，并围绕第四声进行声调教学。本研究为探索「大华语」（陆俭明，2005、2015；李宇明，2017）的语音「共核」（Common Core）（祝晓宏，2019）提供了实证研究的材料与观点，同时为以传意为目标的普通话语音教学观提供了理据。 <br/>This study investigates the Putonghua pronunciation of Cantonese-speaking students in a Chinese communication course at a Hong Kong university, focusing on the phonetic elements that impact “speech intelligibility” (Smith &amp; Nelson, 1985; Munro &amp; Derwing, 1995). The analysis of 126 low-intelligibility syllables produced by 19 speakers revealed that (1) Among single-component errors, vowel errors were the most prevalent, followed by consonant errors; (2) In error combinations, “consonant + vowel” were the most common; (3) Within consonant errors, mispronunciations of “sh” occurred most frequently, followed by errors involving “h,” “x,” “r,” “j,” and “zh”; (4) For vowel errors, “i” was the most commonly mispronounced, particularly in vowels with medial glides; (5) Tone errors were dominated by mispronunciations of the fourth tone, with occasional confusion between the second and third tones. The findings suggest that in Putonghua teaching aimed at Cantonese native speakers with communication as the goal, teaching initials and finals could take precedence over tones, focusing on teaching apical post-alveolars and alveolo-palatals (especially the initials “sh” and “x”), the initial “r”, the monophthongs “i” and “u” and syllables containing medial sounds. Tone teaching should revolve around the fourth tone. This research provides empirical insights and perspectives for exploring the phonetic “Common Core” (Zhu, 2019) under the context of Global Chinese (Lu, 2005, 2015; Li, 2017).

隨著生成式人工智能工具的風潮席捲全球，關於如何革新現有的教育方式和未來教育走向的探討，成為了近年來的熱門話題。香港科技大學鼓勵教學人員使用生成式人工智能工具，語文教育中心在2023年初已經開始了相關的探索。本文僅以筆者負責設計開發的中文核心課程「職場實務中文運用」為例，探討以ChatGPT為代表的GenAI工具在實務中文寫作教學中的運用，並結合學生對在課程中使用ChatGPT效果的反饋進行反思，展望課程以及實務中文教學未來的發展方向。

《詩學綱要》是陳去病（1874－1933）重要的詩學及詩歌史著作。此書本是詩歌史教材，系統論述了中國詩歌自上古至清代之發展與流變，亦旨在匡正時人論詩之流弊。本文集中考察其對宋代與明清詩史的論述，探討陳氏之詩歌史觀及其時代意義。陳氏基於儒家詩教，以性情與氣運為詩歌價值評判之標準；同時又主張「詩以異為體」，強調呈現各代詩家獨特性及差異性之必要。陳氏批評晚清「宗尚蘇、黃」之風氣，持尊唐抑宋立場，延續南社宗唐派對宋詩派之排斥。然其不同於柳亞子（1887－1958）之激烈攻詆黃庭堅（1045－1105），在肯定黃氏師古而能自成一家的同時，通過質疑呂本中（1084－1145）《江西詩社宗派圖》所建構的江西詩派譜系，回應宋詩派的詩歌史話語策略。在明清詩史部分，陳氏持崇明抑清立場，從性情出發，前則肯定復古派嘗試重建文化盛世之氣象，後則表彰明末幾、復諸子之風骨，同時感歎明詩發展遭逢厄運，展現出其對政治盛世下文化理想圖景的嚮往