layer that combines all entries of $H$ to fit the output to respective downstream tasks.

Experiments {#sec:experiments}
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Label-Scarce Educational Problems
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We utilize assessment modeling to exam score (a non-interactive educational feature) and review correctness (a sporadic assessment) prediction. The tasks are described in detail as the following.

### Exam Score Prediction

Exam score prediction (ES) is the estimation of a student’s scores in standardized exams, such as TOEIC and SAT, based on the student’s interaction history in educational system. ES is one of the most important tasks of AIEd, as it is crucial for both students and educational system to assess the performance in a standardized measure. Because a substantial amount of human effort is required to develop or take the tests, the number of data points available for exam score is considerably less than that of student interactions automatically collected by educational systems. By developing a reliable ES model, a student’s score is estimated in a universally accepted score by interactive educational system with considerably less effort. ES differs from student response prediction (e.g. the prediction of assessment $\texttt{response\_correctness}_t$) because standardized tests are taken in a controlled environment with specific methods independent of interactive educational system.

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