The main goal of interactive educational systems is to design optimized, personalized learning paths for students. A primary limitation of these systems is the lack of a final outcome, such as a final exam grade, in student interaction datasets. To address this issue, assessment modeling is introduced as a class of pre-training tasks. In this approach, a deep bidirectional transformer encoder is utilized as the assessment model to evaluate and predict performance.