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纸笔考试智能网上评卷系统的设计和应用——智能教育应用之“考试评价”篇 被引量:15

The Design and Application of the Intelligent Online Marking System for the Pen-and-paper Test——“Examination Evaluation” for the Application of Intelligent Education
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摘要 文章回顾了纸笔考试评卷的发展历程,重点介绍了纸笔考试主观题智能评卷技术和扫描网上评卷技术,并基于这两大技术的融合,设计了纸笔考试智能网上评卷系统。该系统在大规模教育考试网上评卷中的应用,提升了教育考试评卷工作的质量和效率,有助于推动大规模考试评分系统的智能化升级,并为探索人工智能技术与教育考试评卷行业的应用融合形式、构建人工智能技术辅助大规模教育考试网上评卷应用模式提供参考。 This paper reviewed the development of pen-and-paper test marking, emphatically introduced the intelligent marking technology of subjective questions in the pen-and-paper test and the scanning online marking technology, and further designed the intelligent online marking system for the paper-and-pen test based on the integration of the two technologies. The application of this system in the online marking system of the large-scale education examination enhanced the quality and efficiency of the education examination marking work, helped to promote the intelligent upgrading of the marking system of the large-scale examination. In addition, it provided reference for the exploration of the application integration form of the artificial intelligence technology with the marking industry of education examination, and the construction of the application model of the large-scale examination online marking assisted by the artificial intelligence technology.
作者 汪张龙 徐俊 李晓臻 朱玮琳 WANG Zhang-long1, XU Jun1, LI Xiao-zhen2,ZHU Wei-lin1(1. IFL YTEK CO., LTD., Hefei, AnhuL China 230088; 2. iFlytek Institute of Educational Technology, Hefei, Anhui, China 23008)
出处 《现代教育技术》 CSSCI 北大核心 2018年第3期5-11,共7页 Modern Educational Technology
关键词 智能评卷 网上评卷 考试评卷 人工智能 intelligent marking online marking examination marking artificial intelligence
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  • 1王燕.一种改进的K-means聚类算法[J].计算机应用与软件,2004,21(10):122-123. 被引量:9
  • 2Salton G,Wong A, Yang C S. A Vector Space Model for Auto- matic lndexing[J]. Communications of the ACM, 1975,18: 613- 620.
  • 3Blei D, Ng A, Jordan M. Latent dirichlet allocation[J]. Journal of Machine Learning Research, 2003,3 : 993.
  • 4石晶,范猛,李万龙.基于LDA模型的主题分析[J].自动化报,2009,36:1586-1593.
  • 5Wei Xing,Croft W Bo LDA-Based Document Models for Ad-hoc Retrieval[C]//SIGIR' 06. Seattle, WA, USA, August 2006.
  • 6Friedman N, Geiger D, Goldszmidt M. Bayesian Network Classi- fiers[J]. Machine Learning, 1997,2 : 131.
  • 7Doueet A, Godsill S, Andrieu C. On sequential Monte Carlo sam- piing methods for Bayesian filtering[J]. Statistics and Compu- ting,2000,3:197.
  • 8Duda R O, Hart P E, Stork D G. Pattern Classification(2ed)[M].李宏东,姚天翔,等译.机械工业出版社,2003:508.
  • 9Lin J. Divergence measures based on Shannon entropy[J]. IEEE Transactions on Infommtion Theory, 1991,37(14) 145.
  • 10Dikli,S.An Overview of Automated Scoring of Essays[].Journal of TechnologyLearningand Assessment.2006

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