  In this paper, we describe our Knowledge Tracing model for the 2020 NeurIPS
Education Challenge. We used a combination of 22 models to predict whether the
students will answer a given question correctly or not. Our combination of
different approaches allowed us to get an accuracy higher than any of the
individual models, and the variation of our model types gave our solution
better explainability, more alignment with learning science theories, and high
predictive power.
