Monday, July 6, 2026

8:30 AM - 12:00 PM

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Details

Facilitators Joanna Lee Chin Ai, Dr Leong Siew Lian, Mr. Sri Bala Murugan Gogula Nathan, Monash University Aim The workshop aims to support educators in rethinking assessment design in response to the capabilities of generative AI (GenAI). By the end of the session, participants will be able to: Reflect on the implications of GenAI capabilities on traditional assessment formats to identify opportunities for meaningful redesign. Redesign a chosen assessment by evaluating and mapping appropriate GenAI integration points. Apply systematic strategies to align AI utilization with learning outcomes while reflecting on approaches that ensure transparent and visible student learning. Focus This workshop helps participants redesign assessments for the GenAI era. Participants will analyze, develop and redesign an assessment to identify AI permissible tasks and shift focus toward higher-order skills like analysis, evaluation, and problem-solving. Overview GenAI has introduced both opportunities and disruptions for higher education assessment. Prior literature shows that educators are now required to cultivate assessment formats that support self-regulated learning, transparency, and meaningful skill development (Chan, et. al., 2024). Faculty-facing frameworks similarly emphasise the need for structured approaches to redesign, helping educators decide which assessment tasks to retain, adapt, or replace in a GenAI-enabled environment (Nieminen et.al., 2024). This workshop responds to these sector-wide shifts by introducing participants to a framework that balances AI’s capabilities with pedagogical priorities. It’s designed for educators who want to explore practical ways of redesigning their assessments. Workshop plan Participants will be guided through a hands-on experience to redesign assessment by: Applying redesign strategy to transform assessments for GenAI integration. Evaluating and identifying assessment tasks to determine where GenAI integration is appropriate. Mapping and making decisions on AI integration aligned with learning outcomes. Reflect on the redesign process and approaches for ensuring visible student learning outcomes.