Automatic Generation of Standard Examination Questions Based on Ontology

Yi Shan Chen; Dong Ming Ran; Xin Hua Zhu

doi:10.4028/www.scientific.net/AMM.373-375.1747

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 373-375Automatic Generation of Standard Examination...

Automatic Generation of Standard Examination Questions Based on Ontology

Abstract:

Examination question is one of the important tools that reflect students' learning situation and teachers' teaching effectiveness. Traditional questions were generated by the teacher manual, which will lead to the disadvantages of inefficient work and no reusable examination. In order to overcome these disadvantages, the paper proposes an ontology-based approach to standardized examination questions, which automatically generates questions and focuses on the multiple-option questions.

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Periodical:

Applied Mechanics and Materials (Volumes 373-375)

Pages:

1747-1750

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.373-375.1747

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Online since:

August 2013

Authors:

Yi Shan Chen, Dong Ming Ran, Xin Hua Zhu

Keywords:

Automatic Examination System, Domain Knowledge Base, Ontology

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References

[1] Xinhua Zhu, Fangfang Su, Qifeng Tang: A New Ontology-Based Semantic Similarity Algorithm in the Natural Language Processing. Journal of Digital Content Technology and its Applications, 6(12): 188-194, (2012).

DOI: 10.4156/jdcta.vol6.issue2.23

Google Scholar

[2] Ruslan Mitkov and Le An-ha: Computer-aided generation of multiple-choice tests. Proceedings of the HLT-NAACL Workshop on Building Educational Applications Using Natural Language Processing, 17-22, (2003).

DOI: 10.3115/1118894.1118897

Google Scholar

[3] TANG Ya-yuan: Research of papers automatically generated system based on Ontology. China Journal of Hunan University of Science and Engineering, 30(12): 77-80, (2009).

Google Scholar

[4] DING Xiang-min and GU Ming-xia: Summary of Automatic Generation Technology of Multiple-Choice Items. China Journal of modern computer, 15(5): 36-39, (2009).

Google Scholar

[5] LI Ceng, Su Xiao-lu and Qian Pin: The methodology of developing domain ontology. China Journal of Computer and Agriculture, China, 20(7): 7-10, (2003).

Google Scholar

[6] GU Zhi-feng. LiuYong and GUO Gencheng: Improved method of conceptual similarity in ontology mapping. China Journal of Computer Engineering and Applications, 44(8): 67-70, (2008).

Google Scholar

[7] Zhu Li-jun and Tao Lan, Liu Hui: Caculation of the Concept Similarity in domain Ontology. South University of Technology (Natural Science Edition). China, 32(2): 147-149, (2004).

Google Scholar

[8] Lee J, Seneff S: Automatics generation of cloze items for prepositions. INTER SPEECH, 2173-2176, (2007).

Google Scholar