[1]詹沛达,王立君,杨卫敏.引入内容平衡的最大信息量组块分层选题策略[J].江西师范大学学报(自然科学版),2013,(01):106-111.
　ZHAN Pei-da,WANG Li-jun,YANG Wei-min.The Maximum Information Stratification Method with Content Balancing in Computerized Adaptive Testing[J].Journal of Jiangxi Normal University:Natural Science Edition,2013,(01):106-111.
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引入内容平衡的最大信息量组块分层选题策略()
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《江西师范大学学报》（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2013年01期
页码:
106-111
栏目:
出版日期:
2013-01-01

文章信息/Info

Title:
The Maximum Information Stratification Method with Content Balancing in Computerized Adaptive Testing
作者:
詹沛达;王立君;杨卫敏
浙江师范大学教师教育学院心理系,浙江金华,321004
Author(s):
ZHAN Pei-da；WANG Li-jun；YANG Wei-min
关键词:
计算机化自适应测验; 内容平衡; 最大信息量组块分层选题策略; 改良多项式模型
Keywords:
CAT;  content balancing;  MIS-B;  modified multinomial model
分类号:
B841
文献标志码:
A
摘要:
在0-1计分下,为了解决最大信息量组块分层策略(MIS-B)中未考虑内容平衡的问题,通过加入改良多项式模型来平衡内容属性.计算机模拟试验显示:选题策略在保持MIS-B能力估计精准度这一前提下降低了项目重叠率,提高了题库使用均匀性和项目曝光率的均匀性.
Abstract:
In 0-1 scored CAT,a new item selection strategy is proposed to improve the MIS-B method by introducing the Modified Multinomial Model.The results of Monte Carlo simulations show that compared with MIS-B,the approach proposed in this paper can reducing item overexposure rate,balancing item usage within the item bank,and maintaining measurement precision.

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更新日期/Last Update: 1900-01-01