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TMU System for SLAM-2018

2018-06-01WS 2018Code Available0· sign in to hype

Masahiro Kaneko, Tomoyuki Kajiwara, Mamoru Komachi

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Abstract

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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