This study evaluates the effectiveness of three large language models in redacting personally identifying information from discussion forum data in massive open online courses.
The authors examine GPT-4o, Llama 3.3 70B, and Llama 3.1 8B as tools for de-identifying student-generated forum posts.
The study focuses on a key data-use challenge in education research: protecting student privacy while making discussion forum data usable for research and analysis.
By comparing multiple large language models, the article contributes evidence about how AI tools may support de-identification workflows for educational data.