Addressing Two Problems in Deep Knowledge Tracing via Prediction-Consistent Regularization

Understand

Knowledge tracing is one of the key research areas for empowering personalized education.

• It is a task to model students' mastery level of a knowledge component (KC) based on their historical learning trajectories.
• In recent years, a recurrent neural network model called deep knowledge tracing (DKT) has been proposed to handle the knowledge tracing task and literature has shown that DKT generally outperforms traditional methods.
• However, through our extensive experimentation, we have noticed two major problems in the DKT model.