ENGL successfully hosts 2025 “Talking Across the World” Symposium on Global Communication of Chinese Culture in the Digital Age

Set against the background of China’s emphasis on its soft power and global communication, the Research Centre for Professional Communication in English (RCPCE) at our Department successfully hosted this year’s “Talking Across the World” (TAW) Symposium, co-sponsored by the PolyU Faculty of Humanities and the Sin Wai Kin Chinese Humanities Development Fund and features the theme of Global Communication of Chinese Culture in the Digital Age. The two-day event commenced with six plenary talks on 16 May. In the morning, Professor Zhong Weihe from Macau Millennium College, Macau SAR discussed “Innovative Approaches for the Global Communication of Chinese Culture”. His presentation was followed by Professor Wang Lifei’s (Beijing Language and Culture University, Chinese Mainland) “Studies on the Evaluation and Impact of Digital Language Communicability of Chinese Enterprises” and Professor Pang Hui’s (The Chinese University of Hong Kong, Shenzhen, Chinese Mainland) “The Art of Sand Mixing: Huawei’s Translation, Localization and Globalization Practices”. In the afternoon, 45 parallel sessions took place, featuring local and international presenters covering topics related to the symposium theme. The first day was concluded by three other plenary talks, with Professor Zheng Yongyan (Fudan University, Chinese Mainland) introducing “Intercultural education in the age of generative AI: Going beyond the language and cultural boundaries”, Dr Amily Guénier from Lancaster University, United Kingdom, elaborating on the subject of “Communicating Chinese Culture in a Multicultural Environment in the Age of Artificial Intelligence: Insights from Confucius Institutes in the UK and Ireland”, and Mr Gabriele Zanoni from Branding Records sharing his views on “Bridging Cultures: Crafting Global Narratives for Chinese Brands”. The second day of the Symposium (17 May) started with another round of parallel sessions with 30 presentations. Afterwards, Professor William Feng from our Department delivered a talk on “Transculturality in China’s Multimodal Global Communication” at the final Plenary Session. This was followed by Professor Todd Sandel’s (University of Macau, Macau SAR), who discussed “KOL from China: Exploring the intercultural and international communication of China’s social media influencers globally”, wrapping up this year’s TAW Symposium.

Engaging critically with AI-generated content – A Fund for Innovative Technology-In-education Project on AI

AI is reshaping workplaces, yet students often struggle to engage critically with AI-generated content. Our project introduced an AI-driven learning simulation using Classlet, an interactive platform designed to develop AI literacy through structured decision-making, real-time feedback, and multimodal engagement in a VR-based professional office environment. Grounded in experiential learning theory, this approach emphasises active participation, reflection, and iterative improvement. The simulation follows Kolb’s Experiential Learning Cycle, where students engage in concrete AI interactions, reflect on AI-generated responses, conceptualise better prompting strategies, and apply these refinements in real time. Unlike passive AI literacy training, this method ensures that students actively experiment with prompts, analyze AI outputs, and refine their critical thinking skills in AI-assisted workplace decision-making. A key innovation was the simulated intentional exposure to both effective and ineffective AI-generated responses, allowing students to recognise patterns in AI decision-making, refine their prompts, and understand how input structure impacts AI-generated insights. Over a 45-minute session, 21 students completed 646 tasks, engaging in real-world problem-solving using videos, images, and 3D object manipulation. AI-powered avatars facilitated scenario-based discussions, instant feedback loops, and adaptive learning pathways, ensuring that students not only interacted with AI but also reflected on the strengths and limitations of AI-generated insights. Feedback highlighted the engaging and immersive nature of the experience, with students reporting an average enjoyment score of 3.55 out of 5 (equivalent to 71% of the scale’s maximum value). Similarly, the perceived usefulness of the AI learning method received a mean score of 3.48 out of 5 (69.6% of the scale’s maximum value), indicating a generally positive reception of the AI-driven simulation. “It’s innovative and fun,” noted one participant, while others valued the ability to experiment with AI prompts and analyse varying response quality. However, some students struggled with AI continuity, pointing out that "the chatbot skips dialogue sometimes" and that responses felt "too general, needing more follow-up questions." With 99.0% input processing accuracy, the simulation successfully recognised and processed 102 out of 103 student inputs, ensuring that nearly all interactions with the AI were correctly interpreted. Additionally, 96.1% of AI-generated responses aligned with the intended learning objectives, meaning that most outputs provided contextually relevant and meaningful feedback that supported students' learning goals. Future iterations will refine AI response depth using Retrieval-Augmented Generation (RAG) and improve interface design and dialogue. This project under the Faculty of Humanities Fund for Innovative Technology-In-education (FITE) is led by Prof. Renia Lopez, with Prof. Christy Qiu as the co-investigator.

New Paper on understanding online advice-giving evaluations through the politeness evaluation model

This new paper by our Dr Rickey Lu, published in the Journal of Politeness Research, investigates perceptions and evaluations of advice through an experiment that explores different advice formulations. Designed to test the effect of different linguistic formulations of advice, this study examines how participants evaluated advice as manipulated in different experimental conditions. In particular, this paper reports on how these evaluations often invoke different aspects of Spencer-Oatey and Kádár’s politeness evaluation model. Moreover, the findings provide evidence that manipulating the linguistic features of advice can make certain aspects of the politeness evaluation model more salient for evaluation. The implications of this experiment point toward a possible relationship whereby linguistic realizations resonate across psychological and pragmatic dimensions of an interaction. More information of the article can be found HERE.

Interview with Prof. Daisy Zou on AI and Chatbot-Assisted Learning in Humanities

1. What inspired you to explore AI and chatbot-assisted learning for logic development in English argumentative writing? My research was motivated by the growing need for AI-enhanced educational tools that support critical thinking and writing skills. Many English as a Foreign Language (EFL) learners struggle with logical reasoning in argumentative writing, often producing fallacies that weaken their arguments. AI-driven chatbots offer a scalable and interactive way to train students in logic and reasoning, providing instant feedback and personalised learning experiences. 2. How do chatbots improve students’ ability to identify and avoid logical fallacies in argumentative writing? Chatbots provide structured, interactive learning experiences that help students recognise and correct logical fallacies. Through real-time dialogues, chatbots can: Present examples of logical fallacies in different argumentative contexts. Offer immediate feedback when students make reasoning errors. Simulate Socratic questioning to guide learners toward logical reasoning. Encourage self-reflection by prompting learners to revise their arguments. Our research found that chatbot-assisted training significantly improved students’ fallacy identification skills, though some learners initially struggled with adapting to the AI-driven approach. 3. What are the key advantages of chatbot-based learning compared to traditional methods? Chatbot-based learning offers several advantages: High interactivity: Learners can engage in simulated debates and reasoning exercises. Personalised learning paths: AI adapts to the learner’s pace and progress. Instant feedback: Unlike traditional classroom instruction, chatbots provide immediate corrections and explanations. Reduced cognitive load: Learners receive guidance in digestible segments, making complex concepts more approachable. However, chatbots should complement rather than replace human instruction, as nuanced reasoning and debate still require human expertise. 4. What challenges do students face when using chatbots for logic learning? Some students find AI-driven learning intimidating at first, especially when dealing with abstract concepts. Common challenges include: Over-reliance on AI: Some learners expect the chatbot to generate answers rather than engaging critically. Lack of human interaction: While chatbots provide structured learning, they cannot replicate the depth of teacher-led discussions. Varying engagement levels: Students who enter a “flow state”—a deep focus on learning—tend to perform better, but achieving this state varies across individuals. Our research suggests that skill-challenge balance and interactive feedback are crucial for maintaining engagement. 5. How does AI-based logic training impact students’ confidence in writing? Interestingly, while chatbot-based training improves logical accuracy, it may reduce students’ writing self-efficacy in the short term. This happens because as students become more aware of their reasoning errors, they may feel less confident in their writing ability. However, over time, continuous practice with chatbots enhances both logical proficiency and confidence, especially when integrated with traditional writing instruction. 6. How do you see the role of AI evolving in writing instruction? AI is shifting writing instruction from grammar-focused correction to critical thinking and logical structuring. In the future, AI-driven tools will likely: Provide adaptive writing prompts based on learners’ proficiency. Offer real-time argumentative feedback that goes beyond grammar. Integrate multi-modal learning, combining text, speech, and visuals for deeper engagement. AI should empower learners, helping them refine their reasoning while preserving their authentic writing voice. 7. How do you ensure that chatbot-assisted learning remains engaging and effective? To maximise engagement, chatbot-based learning should incorporate: Game-based elements: Encouraging competition and achievement. Conversational interactions: Mimicking real-life debates to promote deeper thinking. Personalisation: Adapting learning content to students’ needs. Our research proposes the RAISE model—Repetitiveness, Authenticity, Interactivity, Student-centeredness, and Enjoyment—to guide chatbot-assisted learning design. 8. What are the future directions for AI in language learning and the humanities? Future advancements will likely include: AI-driven argument analysis: Detecting logical strengths and weaknesses in real time. Emotion-aware AI tutors: Adjusting responses based on students’ engagement and frustration levels. Cross-disciplinary applications: Using AI to enhance critical thinking not only in writing but also in social sciences and philosophy. Ultimately, AI should be seen as a collaborator rather than a replacement—enhancing, rather than diminishing, human creativity and critical reasoning.

Student conference showcases success of Gifted Education Fund programme

The student conference for the Cultivating English Language and Digital Literacies for Future Leaders programme, funded by the Gifted Education Fund from the Education Bureau of the Hong Kong SAR Government (EDB), was successfully held on 25 January 2025 at The Hong Kong Polytechnic University (PolyU). This event marked the culmination of a year-long initiative designed to enhance gifted students’ academic, digital, and professional workplace literacies. The programme was organized by a dedicated team from the Department of English and Communication (ENGL), including Prof. Christy Qiu, Prof. Jenifer Ho, Prof. Jeffry Oktavianus, Dr Molly Pan, Dr Bruce Wang, and Dr Hassan Nejadghanbar, with support from student assistants Miss Nicole Wang and Miss Wenjing Zeng. It engaged 22 students from 17 Hong Kong secondary schools. Over four phases, students participated in courses on academic, digital, and workplace literacies, followed by individual research projects guided by ENGL academic advisors. The conference featured presentations of students’ research projects and was attended by Mr Borromeo Li (EDB representative), Prof. Xiangen Hu (Director of PolyU’s Institute for Higher Education Research and Development), Prof. Eric Friginal (Head of ENGL), and over 30 teachers, parents, and guests. Through the programme, students significantly advanced their English literacy by mastering academic writing, critical reading, and effective communication. Their digital literacy was strengthened through hands-on experience with digital tools, multimedia creation, and data analysis. These skills, combined with enhanced creativity, critical thinking, and self-learning abilities, have prepared students to excel as future leaders in an increasingly digital and interconnected world.

Transforming Language Teaching in the Age of Generative AI

A look into an upcoming book on audio and video-based teaching in the age of generative AI by Prof. Eric Friginal and Prof. Jenifer Ho. As teacher-researchers at the Department of English and Communication (ENGL), our expertise lies at the intersection of language teaching and learning, communication, and technology. We have embraced the mission to transform language teaching through audio, video, and AI technologies by sharing our insights and experiences with language teachers. In our upcoming book, Effective Audio and Video-Based Language Teaching Practices in the Age of Generative AI (Routledge), we aim to provide a hands-on guide for language teachers seeking to enhance their language teaching and assessment practices by incorporating audio and video-based technologies in the design of teaching materials and assessments, with the assistance of Generative AI in material creation. The book offers practical strategies to empower teachers to become content creators without requiring advanced technical skills. The rapid advancement of digital technologies has brought unprecedented changes to language teaching. The move from traditional classrooms to hybrid learning environments, the emergence of digital technologies and social media platforms, and the revolutionary development of Generative AI have placed new demands on teachers to become open to new possibilities in language teaching and assessments. No longer the sole gatekeepers and transmitters of knowledge, language teachers now play a crucial role as facilitators co-constructing knowledge with students. The rise of Generative AI, in particular, is transforming the landscape of language teaching. It challenges language teachers to rethink language teaching and assessment practices to prepare students for the evolving communicative demands which includes the effective use of technologies and multimodal resources to communicate. This shift underscores the urgent need for teachers to integrate technologies - especially audio and video-based tools that mirror the kind of media learners engage with in their daily lives - into language teaching materials to create authentic language learning environments. This change calls for the expertise of applied linguists to provide practical guidance for teachers in navigating this complex terrain. This book is a call to action for language teachers to embrace technologies that bring innovation to language teaching and assessment practices, thereby nurturing students to be ‘future-ready’ in this rapidly changing world. Instead of viewing technologies as replacing language teachers, we remain confident in our leading role in empowering language teachers and learners to harness the potential of technology through our cutting-edge research. ** Using the text provided above and uploaded to an AI video platform (HeyGen), a podcast-style interview was generated, as shown below. This AI technology can transform a written piece into a simulated TV interview using just a brief excerpt. While the results aren’t perfect and may contain some errors, the process of design and creation has been drastically accelerated by AI.   Some discussion questions that could be used in the classroom after viewing this short clip: 1. How does the female speaker’s use of discourse markers reflect the natural flow of conversational speech? Discuss whether these markers enhance the authenticity of the AI-generated dialogue or if they feel artificial or overused in this context. 2. In what ways do the speakers' backchannels and overlaps mirror the dynamics of real-life conversations? Consider whether these elements contribute to a sense of spontaneity or if there are moments where their timing feels awkward or forced. 3. What specific parts of the AI-generated interview feel unusual compared to natural human speech? Reflect on how factors like pacing, tone, or the placement of interruptions and overlaps may differ from the rhythm of an actual interview. Could these differences affect how the audience perceives the content?

Interview with Prof. Phoebe Lin on GenAI-Enhanced L2 Writing Pedagogy

 1. What motivated you to develop a GenAI-enhanced L2 writing pedagogy? My motivation stemmed from recognising the transformative potential of GenAI tools like ChatGPT in language learning. Initially, many viewed GenAI as a simple productivity tool, but I saw an opportunity to integrate it more meaningfully into the writing process. I wanted to move beyond ad-hoc prompt engineering tips to create a structured pedagogy that leverages GenAI to enhance the cognitive and creative aspects of L2 writing. 2. How does your GenAI-enhanced L2 writing pedagogy differ from traditional approaches? Traditional L2 writing instruction often focuses heavily on grammar and vocabulary. However, in the GenAI era, these aspects have become less critical as AI can handle them efficiently. My pedagogy shifts the focus to content creation—encouraging students to develop original, thought-provoking, and logically structured ideas. GenAI acts as a conversational partner, helping students refine their thoughts while maintaining the authenticity and originality of their work. 3. Can you describe the structure of your GenAI-assisted writing course? The course runs for seven weeks and is designed around a process-writing approach. It begins with an introduction to GenAI-enhanced writing, followed by stages where students submit essay ideas, practice GenAI-assisted writing strategies, and receive personalised feedback. Key features include open sharing of ideas on platforms like Padlet, one-on-one consultations, and a strong emphasis on content originality over linguistic perfection. 4. How did students respond to using GenAI in their writing process? Responses varied, but there was a notable positive shift by the end of the course. Initially, some students were sceptical, viewing GenAI as a potential threat to human creativity. However, as they engaged with the pedagogy, many found that GenAI helped them organise their ideas, eliminate redundancies, and reduce writing anxiety. By the end of the course, a majority of students appreciated GenAI’s role in enhancing their writing process. 5. What challenges did you encounter when integrating GenAI into your writing pedagogy? One of the primary challenges was addressing misconceptions about GenAI’s capabilities. Some students initially relied on GenAI to generate entire essays, leading to uninspired and generic content. I had to emphasise that GenAI should be used to support, not replace, the writer’s original thinking. Another challenge was ensuring students developed the necessary skills to critically evaluate GenAI’s feedback and outputs. 6. How do you address concerns about academic integrity when using GenAI tools? I encourage transparency and ethical use of GenAI. The key is to treat GenAI as a tool for brainstorming and refining ideas, not as a ghostwriter. In my courses, students are expected to disclose how they used GenAI in their writing process. This approach fosters a healthy relationship with technology, where students leverage its strengths while maintaining their academic integrity. 7. In what ways has GenAI changed the landscape of L2 writing education? GenAI has levelled the playing field by reducing barriers related to grammar and vocabulary proficiency. This shift means that students are now evaluated more on the quality and originality of their ideas. It has also introduced new pedagogical strategies, such as using GenAI for interactive brainstorming sessions, which can make the writing process more engaging and less intimidating for L2 learners. 8. What future directions do you see for GenAI in L2 writing pedagogy? I envision more personalised and adaptive GenAI tools that can cater to individual learners’ needs, offering tailored feedback and guidance. There is also potential for integrating multimodal features, such as voice interactions and real-time feedback on non-verbal cues, to further enhance the writing process. Ultimately, the goal is to create a dynamic, student-centred learning environment where GenAI complements and amplifies human creativity.

Newly published anthology on aviation English language research

Introducing "Global Aviation English Research", a recently published anthology co-edited by our Head of Department, Prof. Eric Friginal, and published by Bloomsbury Publishing. This comprehensive volume highlights best practices in aviation English language research and thoroughly examines the practical, policy-based, and societal contexts surrounding the ICAO - International Civil Aviation Organization language standards. Featuring contributions from renowned academic experts and aviation professionals, this anthology provides an in-depth analysis of the language needs within the aviation industry, exploring future trajectories and advancements. Through meticulous engagement with research data, case studies, and real-world examples, the volume addresses interactional tasks, transactional exchanges, and radiotelephony. Additionally, it scrutinises the requisite vocabulary and phrasal patterns essential for effective communication across various aviation roles and contexts. We invite everyone to delve into this essential resource, which promises to be an invaluable addition to the field of aviation English research. Learn more about this publication here.

Roman Empire Metaverse Simulation - a Teaching Development Grant Project on AI

Traditional history education often relies on textbooks and lectures, which limit student engagement with historical events and innovations. The absence of interactive learning methods makes it difficult for students to engage in critical thinking about historical decision-making, technological advancements, and their broader societal impacts. The Roman Empire Metaverse Simulation, developed in Classlet, introduced an interactive approach to history learning by integrating AI-driven mentorship, scenario-based inquiry, and multimodal learning methods. Students engaged in structured activities, interacting with AI avatars representing Dio Cassius, Seneca, and Emperor Vespasian to explore Roman architecture, ethical trade-offs, and cultural influence. The AI avatars acted as dynamic guides, adapting their responses based on student input and prompting critical thinking. One student noted, "It's great that they also ask you questions, which leads to more thought and discussion," while another appreciated the game-like interactivity, stating, "It is interesting as the way of interacting with the NPCs is like playing a game." The simulation also integrated 3D object manipulation and artifact analysis, allowing students to examine Roman engineering principles hands-on, rather than passively absorbing content. Through these immersive interactions, students engaged in reflective decision-making, historical comparisons, and experiential problem-solving, strengthening their understanding of Roman society’s complexities. Students responded positively to the interactive and inquiry-driven format, highlighting its engaging, self-paced nature and stronger retention through gaming-based learning. One participant stated, "It’s easier for me to memorize information through gaming—it’s more immersive and interesting." The integration of AI-driven discussions and multimodal exploration provided an adaptive learning experience, encouraging independent reasoning and personalized engagement with historical content. Survey results showed ease of use at 4.00/5, engagement at 3.75/5, and perceived usefulness at 3.71/5. However, some students noted challenges with navigation and response lag, suggesting areas for refinement. By combining AI-driven inquiry, decision-based exploration, and hands-on artifact engagement, the Classlet simulation bridged the gap between passive history education and active historical analysis. Future developments will enhance AI responsiveness, refine interface usability, and expand contextual learning pathways to further support critical thinking, engagement, and adaptability in historical education. The project is led by Prof. Renia Lopez, with Prof. Phoenix Lam, and Ivan Lau as the co-investigators.

Interview with Prof. Daisy Zou on AI-Driven Learning and Cognitive Engagement in Humanities

1. How do you see AI transforming cognitive engagement in learning, particularly in the humanities? AI has the potential to reshape cognitive engagement by making learning more interactive and adaptive. In traditional humanities education, students often engage with static texts and lectures. AI-driven tools, particularly chatbots, can: Facilitate active learning by prompting students with Socratic questioning. Provide immediate cognitive scaffolding, helping learners make logical connections. Encourage deeper processing by engaging students in real-time, structured debates. In chatbot-based logic learning, we observed that students who interacted more actively with AI experienced higher levels of cognitive immersion, leading to stronger retention of logical principles.  2. How do chatbots contribute to self-regulated learning? Chatbots empower learners by promoting self-regulated learning in several ways: Metacognitive support: AI can prompt students to reflect on their reasoning processes. Cognitive engagement: Through structured exercises, learners actively construct knowledge rather than passively receiving information. Personalised feedback: AI adjusts explanations based on learners’ responses, helping them identify gaps in understanding. Our study found that students who used chatbots for logic training developed stronger self-monitoring skills, which helped them refine their writing independently.  3. Your research suggests that chatbot-based learning can lead to a state of “flow.” Can you explain what this means and why it matters? Flow is a state of deep engagement where learners feel fully absorbed in an activity. In AI-assisted learning, flow is triggered when: The task difficulty matches the learner’s ability level. Clear goals are set, so learners know what to achieve. Instant feedback maintains motivation. Our study showed that playability and skill-challenge balance were key factors in maintaining flow in chatbot-based learning. Students who entered this state performed better in logical reasoning and reported higher enjoyment in learning.  4. What role does AI play in developing argumentation skills in non-native English speakers? Many EFL learners struggle with structuring arguments logically. AI can bridge this gap by: Providing structured templates that guide students in forming coherent arguments. Detecting logical inconsistencies and prompting learners to revise weak points. Simulating debates where students practice rebuttals and counterarguments. We found that AI-enhanced training improved students’ ability to construct well-reasoned arguments, particularly in recognising flawed reasoning patterns.  5. One of your studies compares chatbot-based learning with traditional web-based learning. What were the key findings? We compared chatbot-based learning to traditional website-based instruction for logical fallacy training. Key findings included: Chatbots were more effective in improving motivation and engagement. Websites provided better structured information retrieval but lacked interactivity. Students using chatbots reported higher autonomy and confidence in identifying logical fallacies. While websites allowed students to review content at their own pace, chatbots actively guided learners through reasoning exercises, making learning more dynamic.  6. Can AI improve writing quality beyond grammar correction? Absolutely. Many AI tools focus on surface-level grammar correction, but AI-driven learning can enhance deep-level writing skills by: Encouraging logical coherence: AI highlights gaps in reasoning. Providing targeted feedback: Instead of generic suggestions, AI tailors feedback based on a learner’s argument structure. Enhancing critical thinking: AI poses counterarguments, prompting deeper analysis. In chatbot-based writing training, students not only wrote more accurately but also developed stronger argumentative reasoning over time.  7. How do learners emotionally respond to chatbot-assisted learning? Many assume AI-driven learning is impersonal, but our research suggests otherwise. Chatbots can foster emotional engagement through: Conversational interactions that reduce writing anxiety. Encouraging prompts that keep learners motivated. Adaptive responses that make learning feel personal. Students in our study reported that chatbot-assisted learning felt like an ongoing dialogue rather than a rigid instruction process, making them more comfortable experimenting with new ideas. 8. What future innovations do you foresee in AI-enhanced humanities education? Looking ahead, AI will likely: Integrate emotion-aware technology, adapting responses based on student engagement. Enable multi-modal AI learning, combining text, voice, and visual cues. Provide real-time argument assessment, helping students refine their reasoning dynamically. These advancements will not replace human educators but enhance personalised learning experiences, making education more adaptive and interactive.  This interview showcases Prof. Daisy Zou’s pioneering contributions to AI-enhanced learning, highlighting cognitive engagement, self-regulation, emotional response, and future innovations in AI-driven humanities education.