| 改进的最大优先级指标方法 |
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| 引用本文： | 潘奕娆,丁树良,尚志勇. 改进的最大优先级指标方法[J]. 江西师范大学学报(自然科学版), 2011, 35(2): 213-215 |
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| 作者姓名： | 潘奕娆 丁树良 尚志勇 |
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| 作者单位： | 江西师范大学计算机信息工程学院,江西,南昌,330022 |
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| 基金项目： | 国家自然科学基金，教育部人文社科项目，江西省研究生创新专项基金 |
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| 摘 要： | 对程莹提出的最大优先级指标方法中会出现违反约束条件及偏向选择相对约束条件少的项目的情况进行改进,并通过蒙特卡洛模拟考察改进的最大优先级指标方法与原最大优先级指标方法之间的优劣,研究结果表明:改进的最大优先级指标方法在约束条件控制和能力估计的准确性方面均好于原最大优先级指标方法.
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| 关 键 词： | 选题策略 最大优先级指标方法 非计量学约束 |
The Improved Maximum Priority Index Method |
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| PAN Yi-rao,DING Shu-liang,SHANG Zhi-yong. The Improved Maximum Priority Index Method[J]. Journal of Jiangxi Normal University (Natural Sciences Edition), 2011, 35(2): 213-215 |
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| Authors: | PAN Yi-rao DING Shu-liang SHANG Zhi-yong |
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| Affiliation: | PAN Yi-rao,DING Shu-liang*,SHANG Zhi-yong(College of Computer Information Engineering,Jiangxi Normal University,Nanchang Jiangxi 330022) |
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| Abstract: | Maximum priority index method,advanced by Cheng Ying,sometimes violates constraints and tends to choose those items with less constraints.To overcome the above disadvantages,an improved maximum priority index method is proposed in this study.Monte Carlo simulation is employed to compare the superiority of two methods.Results indicate that the improved maximum priority index method not only controls constraints suc-cessfully but also makes estimates of examinees' abilities more precise. |
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| Keywords: | item selection strategy MPI non-statistical constraints |
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