Abstract:

The wide application of Large Language Models (LLMs) since late 2022 has dramatically reshaped the landscape of translation practice and education. While these technologies raise concerns about the future of human translators, they also offer new opportunities to revolutionize translation pedagogy, particularly in multilingual societies like Hong Kong. This project proposes an innovative AI-integrated curriculum that expands the conceptual boundaries of translation, which emphasizes multimodal communication, translanguaging, and hermeneutic inquiry.

Hong Kong’s unique linguistic ecosystem, characterized by code-switching, Kongish, and multimodal urban discourse, provides an ideal context for this study. Everyday practices such as bilingual notices, code-switching, and AI-powered subtitling and translation for impromptu talks reflect deeply embedded translation processes. These practices foster inclusive communication, making Hong Kong a fertile ground for translation-related pedagogical innovation.

The project aims to develop a curriculum that integrates AI tools with hermeneutic translation theories, and investigate how students can critically engage with AI while enhancing their intercultural communication skills, and explore how translation thinking can be transferred to academic, professional, and community contexts. Empirical methods include classroom action research, longitudinal observation, reflective journals, interviews, and surveys. Fieldwork will be conducted to document translation practices in culturally hybrid urban sites, and students will engage in multimodal tasks such as image-text interpretation, Audio Description (AD), and Subtitles for the Deaf and Hard-of-Hearing (SDH).

This project will generate measurable improvements in students’ translation competencies and foster ethical, creative, and culturally attuned professionals. It will support curriculum renewal at the PI’s university and contribute to Hong Kong’s development as a global hub for inclusive language services. By reconceptualizing translation as a set of transferable communicative competencies, this project tries to offer a sustainable model for translation education in the AI era. In addition, expected outcomes include a peer-reviewed publication contributing to global scholarship on AI-integrated translation education; a self-developed translation competency test measuring students’ AI literacy, critical thinking, and knowledge transferability; and a comprehensive teaching portfolio with fieldwork-based materials, assessment rubrics, and best practice guidelines.

Code:

T0298

Principal Project Supervisors:

• SONG Ge

Keywords provided by authors:

• AI-integrated translation pedagogy
• Multimodal intercultural communication
• Hermeneutic translation theory
• Translation competency assessment
• Inclusive language services.

Start Date:

01 Feb 2026

End Date:

30 Jun 2027

Status:

Ongoing

Result:

This project is designed to deliver three key outcomes that are measurable, transferable, and impactful across educational and professional domains.

• Scholarly publication: The project aims to produce a peer-reviewed academic output, preferably published in a top-tier journal or a reputable edited volume in the fields of translation studies, applied linguistics, or digital humanities. The publication will present the theoretical breakthroughs and pedagogical innovations developed through the project, and contribute to international scholarship on AI-integrated translation education.

AI-enhanced translation competency test: A self-developed, modern translation competency test will be created, with intellectual property rights retained by the project team. This test will assess students’ ability to apply AI tools in translation tasks, intervene critically in AI-generated outputs, and

• transfer translation thinking across domains. The test will include:


• AI applicability: Measured improvement in students’ ability to use AI tools effectively (target: ≥30% improvement from baseline).


• Human intervention and critical thinking: Percentage of students demonstrating advanced analytical skills in evaluating AI translations (target: ≥80%).


• Knowledge transferability: Percentage of students applying translation concepts to academic, professional, and everyday bilingual/multicultural contexts in Hong Kong (target: ≥60%).


• Comprehensive teaching portfolio: A full AI-enhanced teaching portfolio will be developed, grounded in Hong Kong’s linguistic and cultural landscape. It will include:


• Teaching materials: Curated from fieldwork and a self-built parallel corpus of Chinese-English-Cantonese texts (e.g., government notices, bank ads, public campaigns).


• Assessment rubrics: Tailored to different levels of learners:


• Junior undergraduate (Years 1–2): Focus on foundational translation literacy and AI tool awareness.


• Senior undergraduate (Years 3–5): Emphasis on multimodal translation, critical evaluation, and real-world application.


• Postgraduate: Advanced theoretical engagement, research-based translation tasks, and reflective critique.


• Best practice guidelines: Including teaching methods, instructional sequence, suggested tasks for critical thinking and group discussion, and strategies for making AI-enhanced translation competencies transferable across disciplines and industries.

These outcomes will support the long-term development of translation education in Hong Kong and beyond, and equip students with the skills needed to thrive in AI-enhanced multilingual environments.

Impact:

This project is designed to generate measurable and sustainable impact on student learning, both during the project period and beyond. It will enhance students’ translation competencies, critical thinking, and intercultural communication skills in ways that are directly applicable to academic, professional, and community contexts.

• Measurable learning gains

Quantitative evaluation will be used to measure students’ progress in applying AI tools to translation tasks. Based on pre- and post-assessment data, the project anticipates a minimum 30% improvement in students’ ability to use AI platforms effectively, particularly in areas such as prompt design, post-editing, and ethical evaluation. In addition to technical skills, the project also aims to cultivate advanced critical thinking. It is expected that at least 80% of participating students will demonstrate the ability to assess AI-generated translations with a high level of analytical rigor. This includes identifying cultural bias, rhetorical inconsistencies, and ethical concerns, which are skills that are essential for translators working in sensitive or high-stakes contexts. Furthermore, a curriculum is designed to promote knowledge transfer beyond the classroom. At least 60% of students are expected to apply translation thinking in real-world bilingual and multicultural settings, such as workplace communication, intercultural mediation, and public service interactions.

• Integration into courses and programmes

The deliverables, including teaching materials, assessment rubrics, and best practice guidelines, will be embedded into existing courses such as “Introduction to Translation”, “Computer-Assisted Translation”, and “Translation and Intercultural Studies”. These resources will support curriculum renewal and provide a model for integrating AI tools with humanistic translation pedagogy. The framework will also be adaptable for postgraduate courses and professional training modules.

These assessment methods will be aligned with course-level learning outcomes and will be supported by a newly developed rubric on AI-enhanced translation competency, designed to assess students’ ability to apply AI tools responsibly, critically, and creatively in translation contexts. This rubric will also serve

as a staff development tool in the Faculty of Humanities, supporting translation educators and colleagues in linguistics, communication, and education who are integrating AI into language-related teaching. Dissemination sessions and workshops will explicitly focus on how this rubric and related teaching activities can be adapted to a wider range of language and humanities disciplines beyond translation studies.

• Long-term curriculum development

The project will produce a comprehensive teaching portfolio and a self-developed translation competency test with intellectual property rights. These will serve as long-term assets for the department and university, and enable future cohorts to benefit from a structured, AI-integrated translation curriculum. The framework will be updated regularly based on student feedback and alumni input, so as to ensure its relevance and sustainability.

• Transferability to the wider community

Students will apply their enhanced skills in real-world settings through community engagement activities, such as providing translation services for NGOs, SMEs, and cultural organizations. This will reinforce learning while contributing to Hong Kong’s multilingual society. Graduates trained under this framework will be better equipped to reduce language barriers in sectors such as education, healthcare, finance, and public services.

Financial Year:

2025-26

Type:

TDG