IJIET 2019 Vol.9(9): 671-677 ISSN: 2010-3689
doi: 10.18178/ijiet.2019.9.9.1286

Auto-generated Test Paper Based on Knowledge Embedding

Duan Zeng-Hui, Hu Xing-Liu, Hao Guo-Sheng, Luo Fang, He Xiao-Dan, and He Yi-Yang

Abstract—Auto-Generated Test Paper (AGTP) has been deeply studied for many years, however, it is still a difficult problem and the certainty to access the best test paper (TP) is not guaranteed yet. In this paper, we put forward a method for AGTP based on knowledge embedding, which makes AGTP easier and faster. The knowledge to be embedded is studied and the mechanism behind it is analyzed. The embedded knowledge in this paper is from both the constraints of TP and the information of question repository (QR). The experiments validated the proposed method and found it is not only faster but also costs less computational resources to access the best TP than other method, such as evolutionary algorithm. What impressed is that the cost time to access the optimum does not rapidly increase with the size of QR. The knowledge plays the important role in AGTP, especially to efficiently improve the performance of the algorithms.

Index Terms—Auto-generated test paper, evolutionary algorithm, knowledge, population initiation.

Duan Zhen-Hui, Hao Guo-Sheng, He Xiao-Dan, and He Yi-Yang are with the School of Computer Science & Technology, Jiangsu Normal University, Xuzhou, 221000, China (e-mail: hgskd@jsnu.edu.cn).
Hu Xing-Liu is with the College of Intelligent Science and Control Engineering, Jinling Institute of Technology, Nanjing, Jiangsu, 211169, China (e-mail: xinghu8@163.com).
Luo Fang is with the School of Software Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China (e-mail: 18796328906@163.com).

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Cite: Duan Zeng-Hui, Hu Xing-Liu, Hao Guo-Sheng, Luo Fang, He Xiao-Dan, and He Yi-Yang, "Auto-generated Test Paper Based on Knowledge Embedding," International Journal of Information and Education Technology vol. 9, no. 9, pp. 671-677, 2019.

Copyright © 2019 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

General Information

  • ISSN: 2010-3689 (Online)
  • Abbreviated Title: Int. J. Inf. Educ. Technol.
  • Frequency: Monthly
  • DOI: 10.18178/IJIET
  • Editor-in-Chief: Prof. Dr. Steve Thatcher
  • Executive Editor: Ms. Nancy Y. Liu
  • Abstracting/ Indexing: Scopus (Since 2019), EI(INSPEC, IET), EBSCO, Electronic Journals Library, Google Scholar, Crossref, etc.
  • E-mail: ijiet@ejournal.net