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Modeling and Statistical Analysis of Mental Test Data

Modeling and Statistical Analysis of Mental Test Data
心理测试数据的建模和统计分析
批准号:
9704474
负责人:
William Stout
金额:
$30.68万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
1997
资助国家:
美国
项目状态:
已结题
起止时间:
1997-07-01 至 2002-06-30

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中文摘要
翻译
心理测验数据的建模与统计分析 威廉·斯托特 伊利诺伊大学 摘要 本研究涉及多题(项)心理测验数据的概率建模和统计分析。 的 研究者过去曾使用非参数项目应答 理论(IRT)范式来研究考试公平性, 复杂的潜在IRT结构的评估,以及认知 过程/心理测量建模和认知诊断考试考生使用调查员共同开发的统一 认知模型 现在,建议开发一个非参数 项目结构的项目级几何描述 经典的分测验分数水平因子分析法。 计划基于统一模型开发实用的可操作认知测试程序。 拟 为了进一步开发测试偏差程序SIBTEST, 非常需要的方法。 一个跨越这三个方面的实际需要 区域是为了我们的非参数程序进行修改,以匹配 基于可能性的潜在能力估计以及他们的 当前使用的数字正确分数。 这项研究涉及开发数学模型和统计程序,以改善标准化和课堂测试,并改善对考生在此类测试中表现的衡量。 有一个 特别强调根据每个考生的个人测试问题为他/她提供教育上有用的概念掌握概况 提供更公平的测试,以及评估 在一个项目上表现良好所需的技能的实质性复杂性 test. 特别地,期望 (i)为每一项提供最佳衡量指标的说明, (ii)制定更公平的测试,特别是通过告知 关于偏置的未来测试的施工规范 应排除的项目类型,以及 (iii)为教育者提供概念掌握的详细艾德反馈 和非精通的能力, 指导进一步的教学和补救工作。 因为标准化考试在美国越来越普遍, 社会,并注意到他们的看门人的作用,上述工作,如果 成功,应该对美国标准化考试的有效性产生重大影响,实际上可以改善教育 在课堂上的过程。
英文摘要
Modeling and Statistical Analysis of Mental Test Data William Stout University of Illinois Abstract This research involves the probabilistic modeling and statistical analysis of multiple question(item) mental test data. The investigator has in the past used the nonparametric item response theory(IRT) paradigm to study test fairness, the statistical assessment of complex latent IRT structures, and the cognitive process/psychometric modeling and cognitive diagnosis of test taking examinees using the investigator co-developed Unified Cognitive Model. Now, it is proposed to develop a nonparametric item level geometric description of the item structure analogous to the classical subtest score level factor analytic approach. It is planned to develop a practical operational cognitive testing procedures based on the Unified model. It is proposed to further develop the test bias procedure, SIBTEST, in various much needed ways. A practical need cutting across all three areas is forour nonparametric procedures to be modified to match on liklihood based latent ability estimates as well as on their currently used number correct scores. The research involves developing mathematical models and statistical procedures to improve standardized and classroom tests and to improve the measurement of examinee performance on such tests. There is a special emphasis on providing an educationally useful concept mastery profile for each examinee based upon his/her individual test question responses, on providing fairer tests, and on assessing the substantive complexity of skills required for performing well on a test. In particular, it is desired to (i) provide for each item a description of what it measures best, (ii) to produce fairer tests -- in particular by informing the construction specifications of future tests about biased item types that should be excluded, and (iii) to provide for educators detail ed feedback of concept mastery and nonmastery for each individual examinee to be used to guide further instruction and remedial efforts. Because standardized tests are ever more ubiquitous in American society and noting their gatekeeper role, the above work, if successful, should have a major impact on how effective standardized tests in America are and indeed could improve the educational process in the classroom.
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Developing the Foundations for a New Test Theory of Cognitive Diagnosis: The Unified Model Applied to Concept Acquisition and Change in Science
Mathematical Sciences: Modeling & Statistical Analysis of Multivariate, Rank, & Mental Test Data, with Social Science Applications
Mathematical Sciences: Modeling and Statistical Analysis of Rank Data and Psychological Test Data
University of Illinois Teacher Enhancement Project in Statistics Education
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