AI and the Future of Assessment: Transforming Educational Practices
Episode Overview: In this episode of the AI Education Podcast, hosts Dan and Ray, alongside guests Adam Bridgman and Danny Liu, dive into the evolving landscape of academic assessment in the age of artificial intelligence. Recorded in the University of Sydney's own studios, this discussion explores the significant shifts in assessment strategies and the integration of AI in educational settings.
Guest Introductions:
- Professor Adam Bridgeman: Pro Vice Chancellor Educational Innovation at the University of Sydney - focused on enhancing teaching quality across the university. [University bio]
- Professor Danny Liu: Professor of Educational Technologies - dedicated to empowering educators to improve their teaching methods through innovative technologies. [University page - LinkedIn page]
Key Topics Discussed:
- The Persistence of Traditional Assessment Models: Despite the push to digital platforms during the COVID-19 pandemic, traditional assessment methods have largely remained unchanged, continuing the practice of replicating physical exam environments online.
- AI's Role in Rethinking Assessment: The guests discuss how AI challenges the conventional reasons for assessments, advocating for a paradigm shift towards assessments that truly measure student understanding and application of knowledge.
- Two-Lane Assessment Approach: Adam introduces a dual-lane strategy for assessment:
- Lane One: Ensures the rigorous verification of student competencies necessary in professional fields.
- Lane Two: Uses AI to foster skill development in using technology effectively, moving beyond traditional assessment forms to embrace innovative educational practices.
- Implementation Challenges and Solutions: The transition to new assessment models is recognised as a gradual process, needing careful planning and support for educators in rethinking their assessment strategies.
- Inclusivity and Access to Technology: Ensuring equitable access to AI tools for all students is highlighted as a critical aspect of the evolving educational landscape, emphasizing the need to support diverse student backgrounds and technological proficiencies.
- Future Outlook: The discussion concludes with reflections on the potential long-term impacts of AI on educational practices, the necessity of ongoing adaptation by educational institutions, and the importance of preparing students for a future where AI is seamlessly integrated into professional and everyday contexts.
Further Reading:
We recommend these three articles from the team, that give more detail on the topics discussed
- Where are we with generative AI as semester 1 starts?
What to do about assessments if we can’t out-design or out-run AI?
Embracing the future of assessment at the University of Sydney