Judgement is theorized as the evaluative locus of educational integrity within GenAI-augmented authorship¶

Claim · All claims
Evidence · 1 study · theoretical r3 · q1
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q1 i? The paper theorizes judgement—learners' capacity to weigh options, justify academic choices, and assume responsibility—as the mechanism through which integrity is demonstrated and assessed in hybrid human-GenAI work. → Sunaina Sharma 2026

Evidence¶

Sunaina Sharma 2026¶

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

q1 · i? · theoretical · r3

Conceptual-theoretical argument, not an empirical result. The paper distinguishes judgement from reflection (Schön) and metacognition (Zimmerman), calling it "a normative evaluative act exercised under conditions of epistemic uncertainty". No data are reported; the paper explicitly states it does not report empirical findings.

"Judgement is defined here as the learner’s capacity to weigh options, justify academic choices, and assume responsibility in relation to disciplinary standards and ethical expectations"

Discussion¶

Related Claims¶

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• Assessment shifts from the quality of AI-generated text to articulating tasks, justifying prompt choices, and reflexively evaluating AI behaviour — a narrower finding that bears on this claim
• Learners given appropriate materials and prompts can successfully develop, articulate, and elaborate rich epistemic ideals for good models and good sources — related