RETA: Development of Longitudinal Models Linking Student Mathematics Achievement to Instruction Content

RETA：开发将学生数学成绩与教学内容联系起来的纵向模型

• 批准号: 0831581
• 负责人: William Schmidt
• 金额: $ 149.97万
• 依托单位: Michigan State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-15 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0831581&HistoricalAwards=false
• 关键词: RETA; Development; Longitudinal; Models; Linking

The project is to develop and evaluate longitudinal models that examine what and how students learn in the school setting. With a focus on mathematics, it draws on a unique data set gathered by the existing Promoting Rigorous Outcomes in Mathematics/Science Education (PROM/SE) project. This Comprehensive NSF/Math and Science Partnership (MSP) effort involving over 300,000 students in grades 3 through 12 and approximately 4,000 teachers in over 50 districts from the states of Michigan and Ohio collected data over the past 4 years, 2004-2008. It consists of multi-grade curriculum measurements at different time points of (a) student knowledge in multiple content topics and of (b) student's opportunity to learn those topics. The sample of students mirrors that of the nation both in demographics and socio-economic factors. The longitudinal models will involve three important issues: the exposure to important mathematics content students experience over time, (ii) the change in student mathematics knowledge in specific curricular sensitive content areas over time, and iii) how the relationship between these two changes. This enables researchers to develop statistical models and evaluate them for three different longitudinal designs: i) one for synthetic cohorts involving multi-grade measurements at a single time point; ii) a second for true grade cohorts with repeated measurements at multiple time points; and iii) an individual longitudinal model involving repeated measurements at multiple time points. The longitudinal models incorporate three important educational issues : i) students opportunity to learn (OTL) curriculum content, i.e., the exposure students experience over time, ii) the change in student achievement in specific content areas over time, and iii) the relationship between OTL and achievement. The fit with the statistical models developed for each is to be explored, and compared and contrasted for results and conclusions that lead to policy implications. The results promise to inform a national model for the improvement of student achievement.

该项目旨在开发和评估纵向模型，以检验学生在学校环境中学习的内容和方式。它以数学为重点，利用现有的促进数学/科学教育严格成果（PROM/SE）项目收集的独特数据集。这项NSF/数学和科学综合合作项目（MSP）涉及密歇根州和俄亥俄州50多个地区的30多万名3到12年级的学生和大约4000名教师，收集了2004-2008年过去4年的数据。它包括在不同时间点的多年级课程测量(a)学生在多个内容主题中的知识和(b)学生学习这些主题的机会。学生的样本反映了这个国家在人口和社会经济因素方面的情况。纵向模型将涉及三个重要问题：随着时间的推移，学生接触到的重要数学内容，（ii）学生在特定课程敏感内容领域的数学知识随时间的变化，以及iii)这两者之间的关系如何变化。这使研究人员能够开发统计模型并对三种不同的纵向设计进行评估：i)一个用于在单个时间点涉及多个等级测量的合成队列；Ii)在多个时间点重复测量的真实等级队列的秒；iii)涉及多个时间点重复测量的单个纵向模型。纵向模型包含三个重要的教育问题：i)学生学习机会（OTL）课程内容，即学生随着时间的推移所经历的接触，ii)学生在特定内容领域的成绩随时间的变化，以及iii) OTL与成绩之间的关系。将探索与为每个统计模型开发的拟合性，并比较和对比导致政策影响的结果和结论。研究结果有望为提高学生成绩提供一个全国性的模式。