Recalibrate detection as a supplementary layer within multi-layer integrity governance rather than its foundation¶

Strategy · All strategies
Evidence · 1 claim (1 mixed) · 1 study (1 theoretical), q1 · 0 of 1 report an effect size · 1 claim rests on one study

Description¶

The paper recommends that institutions shift integrity governance from detection-based compliance models to structurally embedded assessment design, with detection serving as "a supplementary rather than foundational layer of integrity infrastructure". Detection may support formal adjudication in cases of clear misrepresentation or deliberate outsourcing, but governance mechanisms must prioritize assessment designs that evaluate transparent, justified decision-making.

Design Implications¶

Context¶

Requirements¶

• Institutions must articulate clear expectations recognizing GenAI-augmented authorship as normative and support educators in developing shared understandings of criteria and fairness

Constraints¶

• The paper notes procedural defensibility and regulatory accountability in some systems still require mechanisms supporting formal adjudication

Target Learners¶

• higher education students and educators

Target Learning Goals¶

• institutional cultivation of ethical academic practice

Affordances¶

• Postplagiarism Integrity Framework Responsibility

Claims¶

• Judgement is theorized as the evaluative locus of educational integrity within GenAI-augmented authorship [~W]

Related Strategies¶

• Institutional recommendations: shift from detection to process-oriented assessment, transparent AI-use protocols, and revised integrity policies
• Institutional governance should establish practical conditions supporting AI literacy, learner agency, and critical evaluation rather than relying on prohibition and detection
• Foster communities of practice for AI governance instead of rigid top-down policies
• Position AI detection tools as one component within a broader institutional decision-making process, with regularly updated benchmarks

Examples¶

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Key Sources¶

• Sunaina Sharma. (2026). Educational integrity in GenAI-augmented assessment: making judgement visible. International Journal for Educational Integrity 22:6. https://doi.org/10.1007/s40979-026-00216-y