Adapting English Language Assessment Formats in a Hong Kong University Language Center for the Opportunities and Challenges of the Generative AI Context

In English language teaching, the level of ongoing support from generative AI tools now available to undergraduate students has prompted among educators a rapid re-evaluation of teaching, learning and assessment practices. For assessments, discussion on the potential benefits and challenges has focused on aspects including learner ability, academic integrity, future workplace preparation, and the integration of AI resources into the assessment task process. Traditional assessment formats such as five-paragraph essays, business emails, and narrated presentation recordings are now under scrutiny. More recent assessment innovations such as the digital documentary now also require format revisions for the AI context. These changes also raise key questions about validity, course content and learning outcomes. In higher education, English language centers often deliver a range of courses, including general academic English, discipline-specific subjects and postgraduate skill building, which encompass a wide range of assessment formats to be reconsidered in the age of generative AI resources. This presentation reviews the path being taken by a large English language department in a Hong Kong university for its compulsory English language courses, some of which are taken by several thousand students per year. While set within the evolving institutional AI policy, this departmental approach draws on emerging theories about AI-related language assessment tasks and bases assessment feedback on a competency-based language teaching approach. This creates a foundation to establish a more staged assessment of productive language tasks, which allows the integration of generative AI resources while maintaining focus on language proficiency skills required for academic and future workplace contexts.