课题基金 / 基金详情

Measuring Mathematical Knowledge for Teaching Using Computerized Adaptive Testing

Measuring Mathematical Knowledge for Teaching Using Computerized Adaptive Testing
使用计算机自适应测试测量教学数学知识
批准号:
0634306
负责人:
Stephen Schilling
金额:
$71.14万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2006
资助国家:
美国
项目状态:
已结题
起止时间:
2006-09-15 至 2012-08-31

项目摘要

项目成果

Stephen Schilling的其他基金

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
This proposal draws on efforts beginning in 2000 of researchers at the University of Michigan to develop measures of elementary and middle school mathematical knowledge for teaching; this work comprises the bulk of the NSF funded Learning Mathematics for Teaching (LMT) project. In contrast to conventional assessments of mathematical knowledge (e.g., the SAT or Woodcock-Johnson assessment), these measures investigate the special mathematical knowledge teachers use to work in classrooms with students. One of the key outcomes of this work from the point of view of the NSF Math and Science Partnerships (MSP's) is the flexibility afforded by a library of more than 300 items ranging across the content areas of number concepts, operations, patterns, functions and algebra, and geometry, allowing project directors and evaluators to custom tailor assessment instruments to meet their specific needs and the content and effects of professional development efforts. This proposal seeks to fully exploit the extensive library of items developed as part of the LMT project and the psychometric information gathered using IRT as part of that effort through the creation of a web-based computerized adaptive testing (CAT) assessment. Computerized adaptive testing dynamically assesses subject performance in a particular domain by sequentially selecting items from the library in order to maximize the precision of measurement. After a subject has responded to a selected item, her/his scale score is updated, and a new item is chosen to match her/his updated scale score estimate. This process is then iterated until a specified level of precision is reached. The additional precision and reduction in testing time and effort afforded by computerized adaptive measures of teacher knowledge should enhance the ability of MSP project directors and evaluators to judge the efficacy of professional development aimed at improving teachers' content knowledge for teaching; and to estimate the effects of curriculum materials designed to improve teachers' knowledge of mathematics and students. These CAT measures will be accessible to users with limited technical expertise, comparable across a wide variety of programs and approaches to professional development, and will employ the most modern and technically up to date approaches for CAT assessments.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Faster Mixing Markov Chain Monte Carlo for Multidimensional IRT and Cognitive Diagnosis Models
海外基金