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An automatic short-answer grading model for semi-open-ended questions
Zhang, Lishan2; Huang, Yuwei3; Yang, Xi3; Yu, Shengquan1; Zhuang, Fuzhen4
2019-07-31
发表期刊INTERACTIVE LEARNING ENVIRONMENTS
ISSN1049-4820
页码14
摘要Automatic short-answer grading has been studied for more than a decade. The technique has been used for implementing auto assessment as well as building the assessor module for intelligent tutoring systems. Many early works automatically grade mainly based on the similarity between a student answer and the reference answer to the question. This method performs well for closed-ended questions that have single or very limited numbers of correct answers. However, some short-answer questions ask students to express their own thoughts based on various facts; hence, they have no reference answers. Such questions are called semi-open-ended short-answer questions. Questions of this type often appear in reading comprehension assessments. In this paper, we developed an automatic semi-open-ended short-answer grading model that integrates both domain-general and domain-specific information. The model also utilizes a long-short-term-memory recurrent neural network to learn the representation in the classifier so that word sequence information is considered. In experiments on 7 reading comprehension questions and over 16,000 short-answer samples, our proposed automatic grading model demonstrates its advantage over existing models.
关键词Machine learning short-answer grading text analysis classification auto-grading
DOI10.1080/10494820.2019.1648300
收录类别SCI
语种英语
资助项目National Natural Science Foundation of China[61807004] ; Philosophy and Social Sciences Research of the Chinese Ministry of Education[16JZD043]
WOS研究方向Education & Educational Research
WOS类目Education & Educational Research
WOS记录号WOS:000480866000001
出版者ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
引用统计
被引频次:30[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://119.78.100.204/handle/2XEOYT63/4431
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Yu, Shengquan
作者单位1.Beijing Normal Univ, Adv Innovat Ctr Future Educ, Beijing, Peoples R China
2.Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China
3.17Zuoye, Beijing, Peoples R China
4.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China
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GB/T 7714
Zhang, Lishan,Huang, Yuwei,Yang, Xi,et al. An automatic short-answer grading model for semi-open-ended questions[J]. INTERACTIVE LEARNING ENVIRONMENTS,2019:14.
APA Zhang, Lishan,Huang, Yuwei,Yang, Xi,Yu, Shengquan,&Zhuang, Fuzhen.(2019).An automatic short-answer grading model for semi-open-ended questions.INTERACTIVE LEARNING ENVIRONMENTS,14.
MLA Zhang, Lishan,et al."An automatic short-answer grading model for semi-open-ended questions".INTERACTIVE LEARNING ENVIRONMENTS (2019):14.
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