Development of Computing-Based Science Investigations for Middle and High School Students

计算已经成为现代科学、技术、工程和数学领域日常实践的一个组成部分。因此，STEM+Computing Partnerships（STEM+C）计划旨在推进新的多学科方法，以及对STEM教学和学习中计算整合的循证理解，以及旨在为K-12计算机科学教学建立证据库的计算学科特定努力，包括在不同人群中。该项目通过开发和测试基于计算的科学调查来解决这一使命，该调查用于大学先修课程（AP）计算机科学原理课程，并用于供中学和高中教师和学生使用的额外学习模块。 该项目将通过罗得岛州内学生群体多样化的全州学校网络实施，并将为参与学校的教师提供专业发展经验。 将要开发的学习模块将数据和观察的使用与计算相结合，以创建模拟或预测自然现象的概念模型，例如地震、海岸弹性、传染病传播趋势、鱼类毒素的生物积累、氡气的发生率。在家庭中，或与新兴社会问题相关的其他现象。 这个设计和开发项目将开发至少六个基于计算的概念验证科学调查，用于科学或计算课程。 每个调查将以核心科学领域（生命科学，物理科学或地球和空间科学）为基础，但学习模块的内容和影响将涵盖广泛的跨学科主题，重点关注需要行为或工程解决方案的社会问题或潜在危害。 每个主题将要求学生从科学或工程出版物中获取数据，或从NASA，NIH，NOAA或USGS等机构维护的国家数据档案中获取数据，并将这些数据纳入自然现象的概念或计算机模型的开发或测试中。 这些调查将与下一代科学标准所倡导的学科核心思想，交叉概念以及科学和工程实践的绩效预期保持一致。 该项目的研究问题将集中在学生和教师使用计算思维理解，学习或教学的技能;计算思维对科学，工程和计算态度的影响;以及影响计算思维学习和教学的因素。 将开发的学习模块将首先在三个职业和技术中心的不同学生群体的AP课程中进行试点，随后在整个合作网络的学校中实施。 项目研究和评估活动的数据将从高等教育合作伙伴、调查活动本身的评估以及课堂调查和评估中收集。

Computing has become an integral part of everyday practice within modern fields of science, technology, engineering, and mathematics. As a result, the STEM+Computing Partnerships (STEM+C) program seeks to advance new multidisciplinary approaches to, and evidence-based understanding of, the integration of computing in STEM teaching and learning, and discipline-specific efforts in computing designed to build an evidence base for teaching and learning of computer science in K-12, including within diverse populations. This project addresses that mission by developing and testing computing-based science investigations for an Advanced Placement (AP) Computer Science Principles course, and for additional learning modules for use by teachers and students in middle school and high school not engaged in AP courses. The project will be implemented through a state-wide network of schools in Rhode Island having diverse student populations, and will provide professional development experiences for teachers in participating schools. The learning modules to be developed will integrate use of data and observations with computing to create conceptual models that simulate or predict natural phenomena, such as earthquakes, coastal resiliency, trends in the spread of infectious diseases, bioaccumulation of toxins in fish, the incidence of radon in homes, or other phenomena associated with emerging societal issues. This design and development project will develop at least six proof-of-concept computing-based scientific investigations for use in science or computing classes. The investigations will each be grounded in the core science fields (life sciences, physical sciences, or Earth and space sciences), but the content and implications of the learning modules will span a broad range of interdisciplinary topics that focus on societal issues or potential hazards that require behavioral or engineering solutions. Each topic will require students to access data from science or engineering publications, or from national data archives maintained by agencies such as NASA, NIH, NOAA, or USGS, and incorporate these data into the development or testing of their conceptual or computer models of natural phenomena. The investigations will be aligned with performance expectations advocated by the Next Generation Science Standards for disciplinary core ideas, crosscutting concepts, and science and engineering practices. Research questions for the project will focus on student and teacher skills in using computational thinking to understand, learn, or teach; the influence of computational thinking on attitudes toward science, engineering, and computing; and factors influencing the learning and teaching of computational thinking. The learning modules to be developed will first be piloted within AP courses having diverse student populations at three Career and Technical Centers, with subsequent implementations in schools throughout the collaboration network. Data for project research and evaluation activities will be gathered from higher education partners, assessments embedded within the investigation activities themselves, and classroom surveys and assessments.