It was not the students' use of a #ChatBot that was the problem, but they were using material found on the internet that itself was created by a hallucinating ChatBot and published without verification!
This is a type of model collapse we will be dealing with not just at universities in the near future.
A student handed in an exam question answer that smelled very ChatGPT-like: Giving extra information I didn't use in the lecture and didn't ask for, giving me a full runnable class when I asked for a method, and using "static" (in Java). I've been teaching Object-Oriented Programming, not static crap. So I asked ChatGPT and got pretty much the same answer as the student handed in. But I was proctoring the exam and the student sat closest to me.
Eric WANG from Turnitin and
Martina SILIANO from Compilatio
Wang starts out by stating that the AI detection tool that they offer is only an enabler for a conversation between a teacher and a student, not a decision tool or something that offers proof.
I jump in saying that the integration of the two tools confuses the issue. Plagiarism is different from AI-text generation.
@DrLancaster
answers the question "Can Machine Generated Text Be Detected?" with a resounding NO*
(* at least not consistently, accurately and automatically).
The students you catch are the ones who are bad at cheating and thus need the most help.
Sonja Bjelobaba notes the difference between humanties and various sciences in research: In humanitis there is no "outside", the research happens in the text. In many other fields, there is the notion of "contributorship" that often elides into authorship.
Serhiy Kvit notes that it was (and still is) a struggle to overcome the Soviet/Russan legacy. Higher Education Institutions lack financial autonomy, focus instead on building their reputations and capitalizing academic achievements. However, a new culture of quality is developing in Ukrainian HEIs. There is a national agency for quality assurance in HEI, called NAQA https://en.naqa.gov.ua/
Our Pre-Print is online at arXiv!
Testing of Detection Tools for AI-Generated Text https://arxiv.org/abs/2306.15666
The working group on Technology & #AcademicIntegrity at the European Network for Academic Integrity https://www.academicintegrity.eu/wp/technology-academic-integrity-working-group/
tested 12 free "AI checkers" and two subscription systems.
"The researchers conclude that the available detection tools are neither accurate nor reliable and have a main bias towards classifying the output as human-written rather than detecting AI-generated text." #AI