What question did this study set out to answer?

To reconceptualise authenticity in assessment within an AI-mediated context and propose actionable design patterns.

November 14, 2025Education SciencesOpen Access

Beyond Detection: Redesigning Authentic Assessment in an AI-Mediated World

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To reconceptualise authenticity in assessment within an AI-mediated context and propose actionable design patterns.
Conceptual analysis of authenticity in the context of AI in higher education
Development of discipline-agnostic learning design patterns
Practical examples of assessment tasks requiring AI collaboration
Proposed design patterns enhance student engagement and ethical judgement
Tasks include critiquing AI outputs and providing process transparency
Reflective artefacts improve visibility of student thinking and reduce reliance on punitive approaches

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Implication

This conceptual account of authenticity demonstrates how assessments can improve collaboration in education, indicating shifts toward AI-integrated tasks.

Cite This Study

Kickbusch et al. (2025) studied this question.

synapsesocial.com/papers/692519acc0ce034ddc35420e https://doi.org/10.3390/educsci15111537

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Implication

This conceptual account of authenticity demonstrates how assessments can improve collaboration in education, indicating shifts toward AI-integrated tasks.

Beyond Detection: Redesigning Authentic Assessment in an AI-Mediated World

Key Points

Discussion

Implication

Cite This Study

Beyond Detection: Redesigning Authentic Assessment in an AI-Mediated World

Key Points

Discussion

Implication

Cite This Study

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