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Speaker's Abstract

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(Kim) Chun Ki Chuang
MPhil Student
Academic Unit of Language and Literacy Education, Faculty of Education
The University of Hong Kong
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Yuen Yi Lo
Professor
Academic Unit of Language and Literacy Education, Faculty of Education
The University of Hong Kong
Title:
"EMI teacher assessment literacy and the potential of AI-powered question generation platform  "
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In English-medium education and other similar bilingual education programmes where students learn content subjects through an additional language (L2), assessment represents one of the most controversial yet under-researched components. Unlike conventional content instruction, EMI assessment must capture students’ development in disciplinary knowledge and L2 academic literacies. This dual-focus presents significant challenges for assessment design, in the sense that assessment outcomes may misrepresent what students actually know and can do. It follows that EMI teachers need to be equipped with knowledge and skills of evaluating and supporting their students, which is also known as their assessment literacy. 

 

This talk will unpack the complexities of EMI assessment and illustrate a conceptual framework capturing the key components of assessment literacy for teachers working in bilingual education programmes. It will then explore the opportunities brought about by the rapid development of artificial intelligence (AI). In particular, it will present the development and pilot testing of an AI-powered question generation platform designed to facilitate assessment design in EMI. The platform is theoretically grounded in the teacher assessment literacy framework and assessment design matrix, which categorises assessment questions by different levels cognitive and linguistic demands. Built using Retrieval-Augmented Generation (RAG) architecture and aligned with Hong Kong secondary curriculum guides for Biology and Geography subjects, the platform helps generate assessment questions accompanied by explicit labels indicating their cognitive and linguistic demands. It also supports multimodal question generation, producing items that incorporate diagrams, graphs, tables, maps and other visual representations characteristic of content subject assessment. By making the underlying assessment framework transparent through AI-generated labels and explanations, the platform aims to scaffold teachers’ development in assessment literacy. 

Chuang Chun Ki (Kim) is a first-year MPhil student at the Faculty of Education, The University of Hong Kong. He holds a BA in Linguistics from HKU and has experience working as a research engineer in educational technology. His current research explores the use of AI to support CLIL assessment design and enhance CLIL teachers’ assessment literacy.
 
 
Yuen Yi Lo is a Professor at the Faculty of Education, The University of Hong Kong. Her research focuses on bilingual education programmes such as English Medium Instruction (EMI) and Content and Language Integrated Learning (CLIL). She is particularly interested in cross-curricular collaboration, assessment and teachers’ professional development in these programmes.
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