Home / Events

AI Assessment

Event Details

Date : 18 Sep (Thu) (Updated), 6 Oct (Mon) & 3 Nov (Mon) 2025

Time : 12:30pm – 1:30pm

Venue : Learning Lab (RRS321, Run Run Shaw Building, Main Campus, HKU)

Speakers:

Prof. Cecilia Chan, Professor, TALIC, HKU
Dr. Wei Dai, Post-doctoral Fellow, TALIC, HKU

[18 Sep 2025 - Updated] Workshop 1 - The Balancing Act of AI in Assessment – Ethics, Scenarios, and AI Literacy

Date : 18 Sep 2025 (Thu) (Updated)

Time : 12:30pm – 1:30pm

Venue : Learning Lab (RRS 321 Run Run Shaw Building, Main Campus, HKU)

Speaker: Prof. Cecilia Chan, Professor, TALIC, HKU

Abstract

This highly interactive workshop explores the ethical challenges of AI use in assessment. Participants will work through realistic scenarios that highlight the grey areas between acceptable and unacceptable AI use—encouraging critical reflection on what counts as support versus misconduct in their own teaching contexts. We will discuss strategies for guiding students toward ethical AI practices by building their AI literacy, helping them understand not just how to use AI tools but when and why. Participants will also be supported to map out clear guidelines for their own disciplines, clarifying what is permitted, what is not, and how to communicate this effectively to students.

[6 Oct 2025] Workshop 2 - Enhancing Feedback with AI: Insights from Research

Date : 6 Oct 2025 (Mon)

Time : 12:30pm – 1:30pm

Venue : Learning Lab (RRS 321 Run Run Shaw Building, Main Campus, HKU)

Speaker: Dr. Wei Dai, Post-doctoral Fellow, TALIC, HKU

Abstract

This interactive workshop explores how AI can enhance assessment and feedback in higher education. Drawing on our research, participants will examine real-life examples of feedback, practical strategies for enhancing feedback and integrating AI into everyday feedback design. The session features live demonstrations of cutting-edge AI-powered feedback tools, showcasing how they can promote students’ uptake of feedback and support meaningful learning. Through hands-on activities, educators will experiment with integrating AI into their own teaching contexts. We will also critically examine the opportunities and limitations of AI in assessment and feedback provision, alongside the ethical considerations it raises, encouraging participants to reflect on how to harness AI while preserving responsible, effective, and dialogic teacher–student communication.

[3 Nov 2025] Workshop 3 - Designing AI-Resilient Assessments Across Disciplines

Date : 3 Nov 2025 (Mon)

Time : 12:30pm – 1:30pm (HKT)

Venue : Learning Lab (RRS 321 Run Run Shaw Building, Main Campus, HKU)

Speaker: Prof. Cecilia Chan, Professor, TALIC, HKU

Abstract

This hands-on, interactive workshop equips educators to design effective, AI-resilient assessments tailored to their own disciplines. Participants will explore practical strategies from the AI Assessment Integration Framework, including performance-based tasks, portfolios, and discipline-specific adaptations that promote authentic learning while managing AI-related risks. The session will also feature an introduction and guided practice with the AI Resilience App—a tool to help educators evaluate and strengthen their assessment designs. Through collaborative activities, participants will apply what they learn immediately, leaving with concrete plans and resources to build assessments that support learning goals and foster responsible AI literacy among students.

Speakers

Prof. Cecilia K. Y. Chan is a Professor in the Faculty of Education and the Teaching and Learning Innovation Centre (TALIC). She has been playing a key role in enhancing engineering and science education, as well as teaching and learning in higher education. Her combined expertise in these fields and multi-cultural experience enabled her to lead and conduct research on topics such as assessment and feedback, experiential learning, technology enhanced learning, artificial intelligence in education and the development and assessment of 21st century skills spanning in education from east to west.

Dr. Wei Dai is a Post-doctoral Fellow at the AI in Education Lab. With a background in software engineering and computer science, she earned her PhD from Monash University. Her research focuses on educational feedback, learning analytics, and the application of artificial intelligence in education, aiming to enhance teaching and learning practices through innovative computational methods.

For information, please contact: