The Role of Executive Function in Mathematics and Science Learning Difficulties of Students with Disabilities

执行功能（EF）缺陷可以解释有或没有残疾的学生数学和科学成绩较低的原因，因此可能是干预的基本目标。目前在这一领域的研究通常依赖于使用较小样本的初高中学生的横断面研究，因此本研究通过在全国代表性的大型纵向数据集中研究低年级学生的执行功能与数学和科学成就之间的关系，填补了一个关键的空白。该研究还将探讨这些科目的表现如何对学生的自我效能感和对数学和科学的看法产生负面影响。该项目的研究结果将为有残疾或有残疾风险的学生的筛查、监测和干预工作提供信息，这些工作可能是最有效的。本项目将使用幼儿纵向研究-幼儿园队列（ECLS-K）数据集来调查执行功能缺陷是否与风险学生和残疾学生较低的数学和科学成绩有关。研究人员将使用生长混合模型来确定EF和科学和数学成就的早期轨迹。ECLS-K数据集是一个庞大的，具有全国代表性的学生群体，从幼儿园到五年级结束。在控制一些混杂变量的同时，研究人员将使用多元回归模型来确定STEM干预的潜在领域。本项目由美国国家科学基金会EHR核心研究（ECR）项目支持。ECR项目强调在该领域产生基础知识的基础STEM教育研究。投资在至关重要、广泛和持久的关键领域：STEM学习和STEM学习环境，扩大STEM参与，以及STEM劳动力发展。该项目支持积累有力的证据，为理解、构建理论进行解释提供信息，并提出干预和创新建议，以应对STEM兴趣、教育、学习和参与方面的持续挑战。

Executive function (EF) deficits may explain lower math and science achievement for students with and without disabilities and therefore may be essential targets for intervention. Current research in this area often relies on cross-sectional studies using smaller samples of middle and high school students and so this study fills a critical gap by examining relationships between executive function and math and science achievement with younger students in a large, nationally representative longitudinal data set. The study will also explore how performance in these subjects could be negatively impacting students' self-efficacy and views toward math and science. The project's findings will inform screening, monitoring, and intervention efforts for students with or at risk for disabilities when these efforts may be most effective.This project will use the Early Childhood Longitudinal Study-Kindergarten Cohort (ECLS-K) data set to investigate whether executive function deficits are related to lower mathematics and science achievement for at-risk students and students with disabilities. The researchers will use growth mixture modeling to identify early trajectories of EF and science and math achievement. The ECLS-K dataset is a large, nationally representative cohort of students followed from Kindergarten until the end of fifth grade. While controlling for a number of confounding variables, the researchers will use multivariate regression models to identify potential areas of STEM intervention. This project is supported by NSF's EHR Core Research (ECR) program. The ECR program emphasizes fundamental STEM education research that generates foundational knowledge in the field. Investments are made in critical areas that are essential, broad and enduring: STEM learning and STEM learning environments, broadening participation in STEM, and STEM workforce development. The program supports the accumulation of robust evidence to inform efforts to understand, build theory to explain, and suggest intervention and innovations to address persistent challenges in STEM interest, education, learning and participation.