TMU System for SLAM-2018
We introduce the TMU systems for the second language acquisition modeling shared task 2018 (Settles et al., 2018). To model learner error patterns, it is necessary to maintain a considerable amount of information regarding the type of exercises learners have been learning in the past and the manner in which they answered them. Tracking an enormous learner{'}s learning history and their correct and mistaken answers is essential to predict the learner{'}s future mistakes. Therefore, we propose a model which tracks the learner{'}s learning history efficiently. Our systems ranked fourth in the English and Spanish subtasks, and fifth in the French subtask.
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