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Using aggregated AI detector outcomes to eliminate false positives in STEM-student writing
0
Zitationen
5
Autoren
2025
Jahr
Abstract
We show how online artificial intelligence (AI) detectors can assist instructors in distinguishing between human- and AI-written work for written assignments. Although individual AI detectors may vary in their accuracy for correctly identifying the origin of written work, they are most effective when used in aggregate to inform instructors when human intuition gets it wrong. Using AI detectors for consensus detection reduces the false positive rate to nearly zero.
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