教育システム情報学会誌
Online ISSN : 2188-0980
Print ISSN : 1341-4135
ISSN-L : 1341-4135
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受験者の能力を考慮した深層学習ベース短答記述式問題自動採点手法
内田 優斗宇都 雅輝
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ジャーナル 認証あり

2021 年 38 巻 3 号 p. 218-228

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Recently, automated short-answer grading (ASAG) methods based on deep neural networks (DNN) have attained high scoring accuracy. However, the accuracy requires further improvement especially for large-scale and high-stakes tests because a slight scoring error will strongly influence many examinees. To improve the accuracy, this study proposes a new DNN-based ASAG method that utilizes examinees’ abilities which are estimated using an item response theory model from their true-false responses for objective exam questions offering with a target short-answer question.

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