Knowing When to Defer: Selective Prediction for Responsible Knowledge Tracing
The episode discusses 'Knowing When to Defer,' a paper showing how knowledge tracing models can improve by quantifying their own uncertainty. Using Monte Carlo Dropout, the model learns to abstain on predictions it is unsure about, boosting accuracy and ensuring responsible AI deployment in education.