Enhancing Your Course Design with AI Co-designer | FALL 2026

Start Date

Wed, 2026-09-09 12:00

Do you find course design rewarding yet time-consuming? Balancing efficiency with quality, aligning learning outcomes with activities and assessments, and keeping students engaged can feel overwhelming. Even experienced instructors sometimes wish for a clearer way to see how all the pieces fit together.

That is where the AI Co-designer, CEI's in-house AI-assisted course design platform, comes in. The AI Co-designer serves as your dedicated Instructional Design partner for crafting course ILOs, assessments, rubrics, and learning activities.

With the AI Co-designer, you can:

streamline individual and collaborative design workflows
evaluate constructive alignment using built-in pedagogical frameworks
reclaim your time for creative and engaging learning experience design

This innovative approach has already earned significant external recognition. Notably, the AI Co-designer was shortlisted for the QS Reimagine Education awards in both 2024 (AI in Education) and 2025 (Best Use of Generative AI). It also received the Excellence in Educational Impact Award at the AIREA 2nd International Competition on AI in Education 2026 (Use of Generative AI). Furthermore, it is a finalist for the eLFA 2026 Teaching Innovation Award and is featured in the Digital Education Council's Best Practices Collection (Curriculum & Learning Design).

Beyond global recognition, this platform is built specifically for HKUST instructors, which means your voice is crucial. As you utilize the platform, your ongoing feedback and participation will directly help us refine the platform to better fit your teaching needs.

Join us for this interactive workshop to explore how the AI Co-designer can support your teaching practice and make the design process more efficient and inspiring.

By the end of this hands-on session, you’ll be able to:

describe the features and the workflow of the AI Co-designer
use prompts to generate course components and constructive alignment mapping tables based on user materials
apply prompt engineering techniques for iterative content refinement
evaluate the applicability and relevance of generated responses using built-in reflection questions
retrieve generated course components from course conversation and syllabus files

Facilitators : Ronald CHOW and Lya LI
Time : 12:30 - 14:00
Venue : Learning Forum (RM 6558, Lift 27-30)