Analytic Score Prediction and Justification Identification in Automated Short Answer Scoring
Analytic Score Prediction and Justification Identification in Automated Short Answer Scoring
复制标题
自动简答评分中的分析分数预测和合理性识别
DOI：
10.18653/v1/w19-4433
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Kentaro Inui
中科院分区：
文献类型：
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作者：
Tomoya Mizumoto;Hiroki Ouchi;Yoriko Isobe;Paul Reisert;Ryo Nagata;S. Sekine;Kentaro Inui
本文提供了一个分析评估学生的简短回答的反应，以期在教学背景下的潜在利益。我们首先提出并形式化了两个新的分析性评估任务：分析性分数预测和理由识别，然后提供了为分析性简答题评分研究创建的第一个数据集。随后，我们提出了一个神经基线模型，并报告了我们广泛的实证结果，以证明我们的数据集如何用于探索简短答案评分中新的和有趣的技术挑战。该数据集可公开用于研究目的。
This paper provides an analytical assessment of student short answer responses with a view to potential benefits in pedagogical contexts. We first propose and formalize two novel analytical assessment tasks: analytic score prediction and justification identification, and then provide the first dataset created for analytic short answer scoring research. Subsequently, we present a neural baseline model and report our extensive empirical results to demonstrate how our dataset can be used to explore new and intriguing technical challenges in short answer scoring. The dataset is publicly available for research purposes.