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Good practice Imported

University of Sydney 'two-lane' assessment for the AI era

Australia · Sydney · See the Australia profile · See the Sydney profile

Evidence: Descriptive / self-reported Top 1% 87/100 · Ask Evidence Copilot about this practice

Instead of an unwinnable AI-detection arms race, Sydney redesigned assessment into two lanes — secure in-person assessment of core capability, and open assessment where AI use is expected — embedded across all 2025 coursework.

University of Sydney 'two-lane' assessment for the AI era

Details

Maturity
Scaling
Promoter
University of Sydney
Keywords
Assessment, feedback & academic integrity, academic integrity, assessment redesign, higher education

Context

Facing the challenge of generative AI in higher education, the University of Sydney moved away from an AI-detection approach toward a redesigned 'two-lane' assessment framework, embedded across its coursework, assessment and academic-integrity policies.

Objectives

The framework aims to preserve valid signals of student learning while also teaching and assessing skilled, ethical use of AI, replacing what the university describes as an 'unwinnable' AI-detection arms race with a transparent, replicable design.

Activities

Lane 1 is secure, in-person assessment that verifies students can demonstrate core knowledge and skills without external aids. Lane 2 is open assessment that expects and develops appropriate AI use. All 2025 coursework assessments were mapped to the two-lane framework, with degree-level assessment plans continuing to roll out.

Conclusions

University reporting frames the approach as a leading and replicable institutional response to AI in assessment, embedded in policy rather than reliant on detection technology, though evidence of its learning impact is still described as emerging.

Implementation

Implementation detail (cost, timeline, staffing, conditions for success) is not yet available for this practice.

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