Validation of the Equity and Access Rubrics for Mathematics Instruction (VEAR-MI)

高质量的数学教学仍然不常见，学生发展数学理解的机会也不平等。对于有色人种和英语不是第一语言的学生来说尤其如此。虽然教育研究在确定被认为是高质量的实践方面取得了进展，但很少有人关注支持历史上被边缘化的学生群体的具体教学实践，特别是当他们参与更严格的数学时。主要目标是验证一套规则，这些规则涉及支持数学课堂公平和机会的教学实践的存在和质量。此外，项目团队将澄清准则中概述的实践与教师观点和知识方面以及学生学习成果之间的关系。该项目将利用现有的两个以数学教师为重点的大规模数据集来制定数学教学质量标准。这些数据集包括近3000个视频记录的数学课程和学生成绩记录，来自三年级到八年级的学生。该研究和开发项目的四个阶段包括培训材料开发、观察和规则通用性研究、编码器可靠性研究和结构分析。数据分析计划包括案例研究、探索性和验证性因素分析以及认知访谈。探索研究preK-12项目（DRK-12）旨在通过研究和开发创新资源、模型和工具，显著提高preK-12学生和教师对科学、技术、工程和数学（STEM）的学习和教学。DRK-12计划中的项目建立在STEM教育的基础研究和先前的研究和开发工作的基础上，为拟议的项目提供了理论和实证依据。该奖项反映了美国国家科学基金会的法定使命，并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，被认为值得支持。

High-quality mathematics instruction remains uncommon and opportunities for students to develop the mathematical understanding are not distributed equally. This is particularly true for students of color and students for whom English is not their first language. While educational research has made progress in identifying practices that are considered high-quality, little attention has been given to specific instructional practices that support historically marginalized groups of students particularly as they participate in more rigorous mathematics. The main goal is to validate a set of rubrics that attend to the existence and the quality of instructional practices that support equity and access in mathematics classes. In addition, the project team will clarify the relationships between the practices outlined in the rubrics and aspects of teachers' perspectives and knowledge as well as student learning outcomes.This project will make use of two existing large-scale datasets focusing on mathematics teachers to develop rubrics on mathematics instructional quality. The datasets include nearly 3,000 video-recorded mathematics lessons and student achievement records from students in Grades 3 through 8. The four phases of this research and development project include training material development, an observation and rubric generalizability study, a coder reliability study, and structural analysis. Data analysis plans involve case studies, exploratory and confirmatory factor analyses, and cognitive interviews. The Discovery Research preK-12 program (DRK-12) seeks to significantly enhance the learning and teaching of science, technology, engineering and mathematics (STEM) by preK-12 students and teachers, through research and development of innovative resources, models and tools. Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for proposed projects.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.