权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Statistical and Psychometric Methods for Measuring the Extent to Which Culturally Responsive Assessments Reduce Cultural Bias

用于衡量文化响应评估减少文化偏见程度的统计和心理测量方法

基本信息

批准号：
2243041
负责人：
Sandip Sinharay
金额：
$ 36万
依托单位：
Educational Testing Service
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2023
资助国家：
美国
起止时间：
2023-05-15 至 2025-04-30
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2243041&HistoricalAwards=false
关键词：
Statistical Psychometric Methods Measuring Extent

项目摘要

This research project will develop a set of statistical tools to analyze data from culturally responsive assessments. Culturally responsive assessments have emerged as a potential solution to the concern that standardized assessments perpetuate social injustice through their content, design, and use. However, few true culturally responsive assessments exist, and there is a lack of proven statistical methods to analyze data from them. This project will use the tools to be developed and data collected by the project personnel to measure the extent to which culturally responsive assessments reduce cultural bias. Scientific products will be disseminated via social media, workshops, and publications in peer-reviewed journals. Open-source software will be developed to make the tools more accessible to a broader audience. The project will engage graduate students in conducting this research, and the investigators will include students from underrepresented groups in their project. The findings and products originating from this project will be useful for scholars across the social, behavioral, and economic sciences. The project also will have implications for society as it will provide a new set of tools to promote social justice.This research project will provide scholars with new tools for producing fair scores from culturally responsive assessments. The project team first will examine several statistical models and approaches to analyzing data from culturally responsive assessments and demonstrate the effectiveness of these approaches using simulated data. The project team then will develop several culturally responsive assessments with the help of a multidisciplinary team of researchers and practitioners. These assessments will be administered to several thousand examinees obtained from a platform such as Amazon Mechanical Turk or Prolific. The newly developed models and approaches will be used to analyze the data. The analyses will focus on measuring the type and extent of cultural bias in standardized tests and determining the extent to which culturally responsive assessments produce more fair and equitable results. The project will produce publicly available principles and guidelines for preparing culturally responsive assessments and user-friendly software and accompanying manual to implement the approaches developed in this project.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.

该研究项目将开发一套统计工具，以分析来自文化敏感评估的数据。标准化评估通过其内容、设计和使用使社会不公正永久化，这一关切已成为一种潜在的解决办法。然而，很少有真正对文化敏感的评估，也缺乏经过验证的统计方法来分析这些评估的数据。该项目将利用项目人员开发的工具和收集的数据，衡量文化敏感评估减少文化偏见的程度。科学产品将通过社交媒体、讲习班和同行评审期刊上的出版物传播。将开发开放源码软件，使更多的受众更容易使用这些工具。该项目将让研究生参与这项研究，调查人员将在他们的项目中包括来自代表性不足群体的学生。该项目的研究结果和产品将对社会、行为和经济科学领域的学者有用。该项目还将对社会产生影响，因为它将提供一套新的工具来促进社会正义，该研究项目将为学者提供新的工具，从文化敏感的评估中得出公平的分数。项目小组首先将研究几种统计模型和方法，以分析来自文化敏感评估的数据，并使用模拟数据证明这些方法的有效性。然后，项目小组将在一个多学科研究人员和从业人员小组的帮助下，制定几项文化敏感评估。这些评估将对从亚马逊土耳其机器人或多产平台获得的数千名考生进行管理。新开发的模型和方法将用于分析数据。这些分析将侧重于衡量标准化考试中文化偏见的类型和程度，并确定在何种程度上对文化敏感的评估能产生更公正和公平的结果。该项目将制定公开的原则和指导方针，以准备文化敏感的评估和用户友好的软件和随附手册，以实施该项目中开发的方法，该奖项反映了国家科学基金会的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。