CAREER: Supporting Model Based Inference as an Integrated Effort Between Mathematics and Science

该项目将为数学和科学教师设计协调教学的机会，以支持在中学采用更连贯的方法来教授基于统计模型的推理。它将帮助教师帮助更多的学生更深入地理解与测量、数据、变异性和推理相关的思想和实践。由于很少有研究表明如何有效地协调数学和科学教育跨学科界限的学习经验，本项目将通过以下方式解决这一差距：(1)创建基于统计模型的推理教学的设计原则，以协调数学课堂上的数据建模教学与科学课堂上的生态教学；(2)产生纵向（2年）证据，证明数学和科学思想是如何随着学生使用日益复杂的建模和推理实践而共同发展的；(3)设计四个集成单元，协调六年级和七年级数学和科学课程的教学，以支持基于统计模型的推理。本项目将采用基于设计的多阶段研究方法，首先观察教师目前与基于统计模型的推理相关的实践。这一阶段的信息将有助于指导研究人员、数学教师和科学教师共同设计单元，将数学课上的数据建模教学与科学课上的生态调查教学结合起来。该项目将通过课堂范例、书面评估项目和访谈等方式，直接观察六年级和七年级学生的思维和学习情况。来自这些方面的研究数据将提供证据，说明学生如何在科学课上使用数学概念，以及他们在科学课上的生态调查如何引发对新的数学工具的需求来进行推论。由此产生的模型将以富有成效的方式整合数学和科学学习，这种方式既敏感于特定的学科学习目标，也敏感于这些思想和实践可以为学生提供更好的近似STEM学科知识生成实践的方式。职业生涯计划是美国国家科学基金会（NSF）的一项全国性活动，旨在为那些通过杰出的研究、优秀的教育以及在其组织使命的背景下将教育和研究结合起来，体现教师学者角色的初级教师提供奖励。本项目由美国国家科学基金会发现研究PreK-12 （DRK-12）项目资助。DRK-12旨在通过研究和开发创新资源、模型和工具，显著提高pre -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。

This project will design opportunities for mathematics and science teachers to coordinate their instruction to support a more coherent approach to teaching statistical model-based inference in middle school. It will prepare teachers to help more students develop a deeper understanding of ideas and practices related to measurement, data, variability, and inference. Since there is little research to show how to productively coordinate learning experiences across disciplinary boundaries of mathematics and science education, this project will address this gap by: (1) creating design principles for integrating instruction about statistical model-based inference in middle grades that coordinates data modeling instruction in mathematics classes with ecology instruction in science classes; (2) generating longitudinal (2 years) evidence about how mathematical and scientific ideas co-develop as students make use of increasingly sophisticated modeling and inferential practices; and (3) designing four integrated units that coordinate instruction across mathematics and science classes in 6th and 7th grade to support statistical model-based inference.This project will use a multi-phase design-based research approach that will begin by observing teachers' current practices related to statistical model-based inference. Information from this phase will help guide researchers, mathematics teachers, and science teachers in co-designing units that integrate data modeling instruction in mathematics classes with ecological investigations in science classes. This project will directly observe students’ thinking and learning across 6th and 7th grades through sample classroom lessons, written assessment items, and interviews. Data from these aspects of the study will generate evidence about how students make use of mathematical ideas in science class and how their ecological investigations in science class provoke a need for new mathematical tools to make inferences. The resulting model will integrate mathematics and science learning in productive ways that are sensitive to both specific disciplinary learning goals and the ways that these ideas and practices can provide a better approximation for students to knowledge generating practices in STEM disciplines. The CAREER program is a National Science Foundation (NSF)-wide activity that offers awards in support of junior faculty who exemplify the role of teacher-scholars through outstanding research, excellent education, and the integration of education and research within the context of the mission of their organizations. This project is supported by NSF's Discovery Research PreK-12 (DRK-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.