期刊
ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2017
卷 10331, 期 -, 页码 594-597出版社
SPRINGER INTERNATIONAL PUBLISHING AG
DOI: 10.1007/978-3-319-61425-0_72
关键词
Auto-grading; SVM; LSTM; Short-answer
Auto-grading short-answers seems to be sufficiently resolved. However, most auto-graders require comprehensive scoring rubrics, which were not always available. This paper used modern machine learning techniques to build auto-graders without expressly defining the rubrics. The result shows that the best auto-grading model is able to achieve a good inter-rater agreement (kappa = 0.625) with expert grading. The agreement can be further improved (kappa = 0.726) if the auto-grading model gave up scoring some of the answers.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据