华南理工大学学报(自然科学版) ›› 2004, Vol. 32 ›› Issue (7): 36-40.

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一个改进的通用成卷模型及其智能算法

田 翔1 肖人岳1 熊赟晖1 邓飞其2    

  1. 1.华南理工大学 应用数学系‚广东 广州510640;2.华南理工大学 自动化科学与工程学院‚广东 广州510640
  • 收稿日期:2003-11-26 出版日期:2004-07-20 发布日期:2015-09-09
  • 通信作者: 田翔(1974-)‚男‚博士生‚讲师‚主要从事系统工程、人工智能、试题库技术等的研究. E-mail:tx-8@263.net
  • 作者简介:田翔(1974-)‚男‚博士生‚讲师‚主要从事系统工程、人工智能、试题库技术等的研究.
  • 基金资助:
    国家21世纪教育振兴行动计划项目 

An Improved General Test Paper-generating Model and Its Intelligent Algorithm

Tian Xiang1 Xiao Ren-yue1 Xiong Yun-hui1 Deng Fe-i qi2   

  1. 1.Dept.of Applied Mathematics‚South China Univ.of Tech.‚Guangzhou510640‚Guangdong‚China; 2.College of Automation Science &Engineering‚South China Univ.of Tech.‚Guangzhou510640‚Guangdong‚China
  • Received:2003-11-26 Online:2004-07-20 Published:2015-09-09
  • Contact: 田翔(1974-)‚男‚博士生‚讲师‚主要从事系统工程、人工智能、试题库技术等的研究. E-mail:tx-8@263.net
  • About author:田翔(1974-)‚男‚博士生‚讲师‚主要从事系统工程、人工智能、试题库技术等的研究.

摘要: 针对现有试题库系统普遍存在的“成卷结果难以使教师从主观上感觉满意”的问 题‚对试卷的“可用性”进行了分析‚增加了“知识点不重复”、“题型、内容及难度分布均 匀”、“最近试卷中的试题不重复”等可用性约束‚改进了现有的成卷模型.提出以“可满足 度”为启发信息的智能成卷算法.通过对高等教育出版社发行的多门试题库的实际使用表 明‚该模型对理、工、医等多种学科具有通用性‚并且完全消除了知识点的重复‚减少了成 卷误差和试题分布不均匀程度. 

关键词: 试题库, 通用成卷模型, 可用性, 智能成卷, 可满足度

Abstract: To overcome the common trouble that the papers generated by many test paper bank systems are unsatisfactory to teachers‚the usability of the generated paper was analyzed‚and an improved model was proposed‚which adds in the usability constraints on“avoiding overlapping knowledge points”‚“evenly distributing the question types‚contents‚ and difficulty levels”and“avoiding the repeat of questions in test papers”.Accordingly‚to solve the model‚an intelligent algorithm was presented based on a heuristic index called satisfiability degree.The improved model and its algorithm were used to generate papers for several test paper banks published by the Higher Education Press.The results show that the model is widely applicable to science‚engineering and medicine test paper banks.Moreover‚it completely avoids overlapping knowledge points‚decreases the paper-generating error and the uneven degree of question distribution. 

Key words: test-item bank, general test paper-generating model, usability, intelligent paper-generation, satisfiablity degree

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