Enhancing Feedback Practices with AI

Date: 27 July 2026, Monday

Time: 1pm - 2pm

Synopsis

This webinar explores how AI can help scale feedback and practice in teaching and learning.

 Session 1 focuses on lecturer–AI co-creation to generate timely, individualised feedback for Self-directed and Collaborative Learning (SDCL). It highlights how tools like Pair can draft feedback, which lecturers then review, align with rubrics, and refine using professional judgement before sharing with students.

 Session 2 demonstrates AI-enabled role-play to support scenario-based practice in skills-focused modules. It combines AI-generated scenarios with lecturer scaffolding, enabling realistic practice within limited time. Key considerations include student participation, speech-based interaction, and maintaining human oversight to ensure meaningful feedback and learning experiences.

Speaker

Jon Rajan (RP)

Jon is a Lecturer at Republic Polytechnic's Centre for Foundational Studies and serves as the Module Chair for Innovation and Practice, where he drives the modernization of academic delivery. He embeds AI into coursework to help students adapt to automation and digital workflows. He also pioneers AI-driven assessment tools that deliver consistent, equitable, and real-time feedback.

Jin Mengqi (RP)

Mengqi is a Lecturer at Republic Polytechnic's School of Applied Science, teaching in the Diploma in Pharmaceutical Science programme. She actively explores the integration of AI-powered tools into curriculum design to create more engaging and personalised learning experiences. Mengqi is passionate about bridging traditional pedagogy with innovative EdTech solutions, empowering students in the pharmaceutical sciences to thrive.