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带区分度约束的选题策略研究
The Item Selection Strategies with Discrimination Constraint
【摘要】 最大优先级指标(MPI)选题策略可以较好地满足非统计性约束,按a分层的选题策略可以有效提高低区分度项目的利用率,结合两者的优势,构造了附加区分度约束的两阶段MPI选题策略.Monte Carlo模拟研究表明:新选题策略在题库的未使用率方面有明显改进,在测量精度和约束条件控制等评价指标上较现有方法差异不大.
【Abstract】 MPI can well meet the statistical constraints,and a-stratified method can effectively improve the utilization rate of low discrimination item. Combining the advantages of MPI and a-stratified method,a two-phase MPI item selection strategy with additional distinction constraint is constructed. The simulation study of Monte Carlo shows that the new item selection strategy has improved a lot in the inavailability of item bank,which is about the same as the existing approach in measurement accuracy,constraint management and other evaluation in dices.
【关键词】 非统计约束;
选题策略;
a分层;
最大优先级指标方法;
【Key words】 the statistical constraints; item selection strategy; a-stratified method; maximum priority index method;
【Key words】 the statistical constraints; item selection strategy; a-stratified method; maximum priority index method;
【基金】 国家自然科学基金(31500909,31360237,31300876,31160203,31100756,30860084);教育部人文社会科学研究青年基金(13YJC880060);江西省教育科学2013年度一般课题(13YB032)资助项目
- 【文献出处】 江西师范大学学报(自然科学版) ,Journal of Jiangxi Normal University(Natural Science Edition) , 编辑部邮箱 ,2016年04期
- 【分类号】B841
- 【被引频次】2
- 【下载频次】104