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

在现代科学、技术、工程和数学领域，计算已经成为日常实践中不可或缺的一部分。因此，STEM计算伙伴关系(STEM C)计划寻求推动新的多学科方法和对计算在STEM教与学中的整合的基于证据的理解，以及特定学科在计算方面的努力，旨在为K-12计算机科学的教学和学习建立一个证据基础，包括在不同的人群中。该项目通过开发和测试高级选修课程(AP)计算机科学原理课程的基于计算的科学调查，以及供中学和高中非AP课程的教师和学生使用的附加学习模块来满足这一使命。该项目将通过罗德岛拥有不同学生人口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把数据和观测与计算机的使用结合起来，以创建概念模型来模拟或预测自然现象，如地震、沿海恢复能力、传染病传播趋势、鱼中毒素的生物积累、家庭中氡的发生率或与新出现的社会问题有关的其他现象。这个设计和开发项目将开发至少六个基于概念验证计算的科学调查，用于科学或计算课程。每个调查都将以核心科学领域(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跨越广泛的跨学科主题，这些主题侧重于需要行为或工程解决方案的社会问题或潜在危险。每个主题将要求学生访问科学或工程出版物中的数据，或从NASA、NIH、NOAA或USGS等机构维护的国家数据档案中获取数据，并将这些数据纳入他们对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对学科核心思想、交叉概念以及科学和工程实践的绩效期望保持一致。该项目的研究问题将集中在学生和教师使用计算思维来理解、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。要开发的学习模块将首先在三个职业和技术中心拥有不同学生群体的AP课程中试行，随后在整个合作网络的学校实施。将从高等教育合作伙伴那里收集项目研究和评估活动的数据、纳入调查活动本身的评估以及课堂调查和评估。

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.