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Doctoral Dissertation Research: Multidimensional Nominal Response Models in Adaptive Testing

Doctoral Dissertation Research: Multidimensional Nominal Response Models in Adaptive Testing
博士论文研究:自适应测试中的多维名义响应模型
批准号:
2119912
负责人:
Jonathan Templin
金额:
$1.2万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-09-01 至 2023-08-31

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英文摘要
This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). This doctoral dissertation research project will investigate the use of multidimensional tests in computerized adaptive testing. Multidimensional tests are used across many disciplines to make critical decisions on issues such as psychological health, educational ability, and vocational suitability. Some of these tests are administered as Computerized Adaptive Tests (CATs), a mode of testing that adapts the test in real time based on the examinee's item responses. Generally, CATs are designed to work with item responses that are scored as 0 or 1, based on whether the examinee has chosen the correct response option or an incorrect response option. However, this dichotomous scoring scheme disregards information contained in incorrect response options, which can be modeled as nominal response data. Research on single-subject CATs has demonstrated that when its components are designed to work with nominal response data, the tests were shorter and more accurate than those designed for dichotomous responses. This project will examine the value of multidimensional adaptive tests that utilize item response options as nominal response data. Psychometric software will be developed and made publicly available. As a Doctoral Dissertation Research Improvement award, support is provided to enable a promising student to establish a strong, independent research career.This research project will advance the use of multidimensional tests in computerized adaptive testing by incorporating item response options into the modeling, item selection, and estimation processes that constitute the adaptive test. The project will compare the accuracy, efficiency, and security of this approach to existing procedures. Adaptive test components and results will be simulated for Multidimensional Adaptive Tests (MATs) and Cognitive Diagnostic-Computerized Adaptive Tests (CD-CATs). Both MATs and CD-CATs can be used for either summative or formative assessment purposes. However, they differ in their theoretical assumptions and thus must be investigated separately. To compare the incorporation of item response options in multidimensional adaptive testing to current dichotomous scoring procedures, item banks and item selection methods will be manipulated. Common item selection methods for dichotomous response data will be generalized for use with nominal response data to ensure comparability.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(1)
专著(0)
科研奖励(0)
会议论文
A model comparison approach to posterior predictive model checks in Bayesian confirmatory factor analysis.
贝叶斯验证性因素分析中后验预测模型检查的模型比较方法。
DOI: 10.1080/10705511.2021.2012682
发表时间: 2022
期刊: Structural equation modeling
影响因子: --
作者: [Zhang, J.]
通讯作者: Zhang, J.
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