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Artificial Intelligence in Assessment Design for Cantonese Education

Sep 2026 · Advances in computational intelligence and robotics book series · pp. 359-386 · 30 references

Abstract

This chapter explores how artificial intelligence reshapes assessment design in higher education, using Cantonese as a second language as a distinctive lens. Cantonese's tonal and sociolinguistic complexity provides a rigorous case for evaluating AI's role in oral proficiency testing. The discussion highlights the shift toward adaptive, learner-centred formats that move beyond standardised methods. Drawing on Hong Kong's higher education practices, it demonstrates how integrating Automatic Speech Recognition, Large Language Models, and Text-to-Speech enables contextualized tasks, real-time feedback, and alignment with ACTFL and CEFR frameworks. It also addresses challenges of transparency, cultural sensitivity, and human-in-the-loop mediation. Ultimately, AI-driven assessment design fosters flexible, inclusive, and pedagogically robust approaches across multilingual higher education.

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