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When traffic lights fail: the case for a two-lane approach to assessment. With Danny Liu

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Manage episode 485215962 series 3598739
Content provided by Phil Martin. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Phil Martin or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Today I'm talking with Danny Liu about assessment in the age of AI. So far, the idea of a 'traffic light' approach to assessment has been gaining traction in higher education in response to the widespread availability of generative AI. Using the traffic light metaphor, assignments are colour coded according to the level of AI use deemed to be permissible. However, as these systems rely solely on student self report on the level of AI use, Danny argues that there is a danger that they lose their value as valid assessment tools.

Danny talks us through the two-lane approach to assessment that has been adopted at the University of Sydney, distinguishing between 'Lane One' supervised assessments aimed at measuring student capability and 'Lane Two' assessments that encourage learning and engagement with AI. We talk through the process of making structural assessment changes, responses from academics, retaining student engagement, and a range of other topics.

Guest bio

Danny is a molecular biologist by training, programmer by night, researcher and faculty developer by day, and educator at heart. A multiple international and national teaching award winner, he works at the confluence of artificial intelligence, student engagement, and educational technology. A Professor of Educational Technologies at the University of Sydney, he co-chairs the University's AI in Education working group, and leads the Cogniti.ai initiative that puts educators in the driver's seat of AI.

Find Danny on Linkedin at https://www.linkedin.com/in/dannydotliu/ and check out the University of Sydney’s AI for Educators resource page at https://canvas.sydney.edu.au/courses/63765

Further reading

Corbin, T., Dawson, P. and Liu, D. (2025). Talk is cheap: why structural assessment changes are needed for a time of GenAI. Assessment & Evaluation in Higher Education, pp. 1–11. Available at: doi: 10.1080/02602938.2025.2503964.

Liu, D. (2025). A "two lane" approach to assessment in the age of AI: Balancing integrity with relevance. Digitally Enhanced Education Webinars. Available at: https://www.youtube.com/watch?v=Hf8-b1H3qOU [accessed 16th May 2025]

Liu, D., and A. Bridgeman. (2023). 'What to Do about Assessments If we Can’t out-Design or out-Run AI? Teaching@Sydney. Available at: https://educational-innovation.sydney.edu.au/teaching%40sydney/what-to-do-about-assessments-if-we-cant-out-design-or-out-run-ai/

  continue reading

22 episodes

Artwork
iconShare
 
Manage episode 485215962 series 3598739
Content provided by Phil Martin. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Phil Martin or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Today I'm talking with Danny Liu about assessment in the age of AI. So far, the idea of a 'traffic light' approach to assessment has been gaining traction in higher education in response to the widespread availability of generative AI. Using the traffic light metaphor, assignments are colour coded according to the level of AI use deemed to be permissible. However, as these systems rely solely on student self report on the level of AI use, Danny argues that there is a danger that they lose their value as valid assessment tools.

Danny talks us through the two-lane approach to assessment that has been adopted at the University of Sydney, distinguishing between 'Lane One' supervised assessments aimed at measuring student capability and 'Lane Two' assessments that encourage learning and engagement with AI. We talk through the process of making structural assessment changes, responses from academics, retaining student engagement, and a range of other topics.

Guest bio

Danny is a molecular biologist by training, programmer by night, researcher and faculty developer by day, and educator at heart. A multiple international and national teaching award winner, he works at the confluence of artificial intelligence, student engagement, and educational technology. A Professor of Educational Technologies at the University of Sydney, he co-chairs the University's AI in Education working group, and leads the Cogniti.ai initiative that puts educators in the driver's seat of AI.

Find Danny on Linkedin at https://www.linkedin.com/in/dannydotliu/ and check out the University of Sydney’s AI for Educators resource page at https://canvas.sydney.edu.au/courses/63765

Further reading

Corbin, T., Dawson, P. and Liu, D. (2025). Talk is cheap: why structural assessment changes are needed for a time of GenAI. Assessment & Evaluation in Higher Education, pp. 1–11. Available at: doi: 10.1080/02602938.2025.2503964.

Liu, D. (2025). A "two lane" approach to assessment in the age of AI: Balancing integrity with relevance. Digitally Enhanced Education Webinars. Available at: https://www.youtube.com/watch?v=Hf8-b1H3qOU [accessed 16th May 2025]

Liu, D., and A. Bridgeman. (2023). 'What to Do about Assessments If we Can’t out-Design or out-Run AI? Teaching@Sydney. Available at: https://educational-innovation.sydney.edu.au/teaching%40sydney/what-to-do-about-assessments-if-we-cant-out-design-or-out-run-ai/

  continue reading

22 episodes

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