PrediQT – Predicting question complexity

The complexity scores generated using this model are based on a Large Language Model trained on thousands of human responses. The model is strongly correlated with human ratings of question complexity.

PrediQT’s scoring is grounded in the hierarchical Bloom taxonomy framework, which classifies cognitive tasks from basic recall through creative synthesis. By aligning the LLM’s continuous outputs to Bloom’s six levels—Remember, Understand, Apply, Analyze, Evaluate, and Create—the app ensures that each complexity score reflects well-established educational standards.