Overview
This site accompanies the WGU-Reddit Analyzer, a capstone project that examines whether large language models can be used to organize unstructured student discussion in a reproducible and inspectable way.
Students frequently discuss course difficulties informally and anonymously in public spaces such as Reddit. This text is noisy, inconsistent, and difficult to analyze using traditional rule-based methods. Recent research shows that large language models can be used to extract and organize recurring themes from Reddit discussions using staged, schema-driven pipelines (Rao et al., 2025). Link to paper
This project uses Reddit posts about WGU courses as a test case to evaluate whether recurring course-level student difficulties can be surfaced reliably using an artifact-based LLM pipeline.
Pipeline overview
A multi-stage LLM pipeline processes a fixed snapshot of Reddit posts. Posts describing student-reported difficulties (pain points) are identified, grouped within courses, aligned across courses, and summarized into precomputed counts and supporting excerpts. These outputs are then published to a static, read-only website.
High-level pipeline used to produce the published snapshot.
The website itself performs no analysis and runs no models. It exists solely to present the frozen outputs of the pipeline in a transparent and inspectable form.