Hi everyone! 👋
I just joined TEN and wanted to introduce myself. My name is Sadaqat, and I am an Assistant Librarian at a university.
In my day-to-day role, I am responsible for handling plagiarism screening for FYP, FRP, BRP, and postgraduate theses. Lately, I’ve been running into a fascinating but challenging roadblock: I frequently get asked by both faculty members and students, "Why can we easily check the similarity index, but we can't definitively check for AI-generated content? "As generative AI continues to reshape academic writing, explaining the technical difference between text-matching (similarity) and predictability modeling (AI detection) to users has become a major part of my workflow.
I would love to know is anyone else in the community facing these same questions from faculty or students? I am very eager to connect with fellow librarians, educators, or tech enthusiasts here to swap notes, share resources, and discuss how we can best navigate this shift in academic integrity!
Best regards,
Sadaqat
3 replies
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Hi , welcome to TEN!
You’re definitely not alone in navigating these questions. If your institution is already using Turnitin, you may also want to explore Turnitin Originality, an add-on that brings AI writing detection and additional academic integrity insights. You can learn more and book a demo here.
I’d love to connect you with others in our community who may be interested in sharing their experiences and perspectives!
We also hold #AskTurnitin discussions here in TEN, where educators share their experiences and perspectives on topics related to teaching, learning, and academic integrity. If you’d like to do a quick backread, here are a few of our recent discussions:
- #AskTurnitin: Month-Long Q&A with the Turnitin Team on Navigating AI in Teaching and Learning
- AI in Education: Exploring Responsible Use Together (#AskTurnitin x ACUE)
- AI with Integrity: Bringing Clarity to the Learning Process #AskTurnitin
- Kat, Turnitin Team
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Hi good to meet you!
I work as a teacher's assistant lead at a small undergraduate college. My sense is that while the faculty at my institution may not all be aware of the technical distinction between similarity detection and AI detection, they nonetheless have a pretty good sense of the limitations of AI-detection software.
What makes similarity detection relatively straightforward is that you are matching the student's writing to already-existing text that is documented online. What makes AI-detection so difficult is that the AI bot is generating new content (even if it is based off already-existing content), so you have to try and predict what AI would do, which is just an inherently tricky task.I know you probably already know that, but maybe that would be a helpful way to explain it to faculty/students.
does Turnitin have a resource that explains the distinction between similarity detection and AI-detection?
Kindly, Tim