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KI-Text in Prüfungsarbeiten erkennen. Probleme und Lösungen

Authors: Kepser, Matthis;

KI-Text in Prüfungsarbeiten erkennen. Probleme und Lösungen

Abstract

Vermehrt tauchen an Schulen und Hochschulen schriftliche Prüfungsarbeiten auf, bei denen die Lehrenden den Verdacht haben, dass sie in großen Teilen KI-generiert worden sind. Aber wie kann ein überzeugender argumentativer Nachweis gelingen? Der folgende Beitrag zeigt dazu zwei Wege auf: der Einsatz von sogenannten Detection Tools am Beispiel von GPT Radar und die händische Analyse von KI-typischen Textmerkmalen. Beide Verfahren sind für sich fehleranfällig, aber zusammen ergeben sie doch eine recht plausible und verlässliche Beurteilungsgrundlage. Dabei ist jedoch zu bedenken, dass sich KI-gestützte Textgeneratoren auf der einen Seite und ebenso Detection Tools auf der anderen kontinuierlich weiterentwickeln. Auch können Schüler/-innen und Studierende versuchen, die Herkunft von KI-generiertem Text bewusst zu verschleiern.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average