Automatic assessment of students' free-text answers with support vector machines

Wen-Juan Hou*, Jia Hao Tsao, Sheng Yang Li, Li Chen

*此作品的通信作者

研究成果: 書貢獻/報告類型會議論文篇章

11 引文 斯高帕斯(Scopus)

摘要

For improving the interaction between students and teachers, it is fundamental for teachers to understand students' learning levels. An intelligent computer system should be able to automatically evaluate students' answers when the teacher asks some questions. We first built the assessment corpus. With the corpus, we applied the following procedures to extract the relevant information: (1) apply the part-of-speech tagging such that the syntactic information is extracted, (2) remove the punctuation and decimal numbers because it plays the noise roles, and (3) for grouping the information, apply the stemming and normalization procedure to sentences, (4) extract other features. In this study, we treated the assessment problem as the classifying problem, i.e., classifying students' scores as two classes such as above/below 6 out of 10. We got an average of 65.28% precision rate. The experiments with SVM show exhilarating results and some improving efforts will be further made in the future.

原文英語
主出版物標題Trends in Applied Intelligent Systems - 23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2010, Proceedings
頁面235-243
頁數9
版本PART 1
DOIs
出版狀態已發佈 - 2010 十二月 1
事件23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligence Systems, IEA/AIE 2010 - Cordoba, 西班牙
持續時間: 2010 六月 12010 六月 4

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
號碼PART 1
6096 LNAI
ISSN(列印)0302-9743
ISSN(電子)1611-3349

其他

其他23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligence Systems, IEA/AIE 2010
國家/地區西班牙
城市Cordoba
期間2010/06/012010/06/04

ASJC Scopus subject areas

  • 理論電腦科學
  • 電腦科學(全部)

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