| dc.contributor.author |
Mphahlele, Ramashego Shila
|
|
| dc.date.accessioned |
2026-04-16T12:45:13Z |
|
| dc.date.available |
2026-04-16T12:45:13Z |
|
| dc.date.issued |
2026-04-16 |
|
| dc.identifier.uri |
https://ir.unisa.ac.za/handle/10500/32381 |
|
| dc.description |
This guide helps students understand why their work might be flagged as AI-generated on Turnitin even when they wrote it themselves. It breaks down how AI detection works, common reasons for false positives, and what you can do to avoid being wrongly flagged. It also addresses fairness concerns and provides tips to protect yourself and to confidently explain your work if needed. |
en_US |
| dc.description.abstract |
This Open Educational Resource (OER) provides students with a clear and critical understanding of Turnitin’s AI detection tool. It explains how AI detection works, why human-written work may be incorrectly flagged, and the limitations of such technologies. The resource also highlights potential biases, particularly those affecting non-native English speakers, and offers practical strategies for students to protect their academic integrity and confidently defend their work. |
en_US |
| dc.rights |
Attribution-NonCommercial-ShareAlike 2.5 South Africa |
|
| dc.rights.uri |
http://creativecommons.org/licenses/by-nc-sa/2.5/za |
|
| dc.subject |
Turnitin AI detection |
en_US |
| dc.subject |
AI-generated content detection |
en_US |
| dc.subject |
Academic integrity |
en_US |
| dc.subject |
Plagiarism detection |
en_US |
| dc.subject |
Student writing |
en_US |
| dc.title |
Understanding Turnitin False Positives |
en_US |
| dc.type |
Presentation |
en_US |