Integration of Environmental Chemistry and Computing to Advance Evidence-based Reasoning, Problem Solving, and Computational Thinking in Middle School Students

在现代科学、技术、工程和数学(STEM)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)计划寻求推进STEM教与学中计算集成的新方法和基于证据的理解。计算思维(CT)是一种智力技能，植根于构思计算机可以有效操纵的有意义的、基于信息的表征的能力。将CT融入核心科学教学解决了K-12教育中的实际限制，因为课程中没有空间直接向每个人教授它。但是，更重要的是，将CT整合到核心科学中提供了一个协同作用的机会，以深化两者的教学。STEM教育计划有效地促进了CT技能的发展，将其作为一项基本能力，是培养未来STEM劳动力方面最成功的项目之一，这些劳动力能够利用计算方法来推进基础科学和工程研究，并设计创新的方法，利用丰富的数据资源来解决复杂的、与社会相关的问题。同样，一个有科学素养的社会越来越需要认识到，科学知识的进步如何与大数据、建模和模拟的使用交织在一起，如果他们要做出知情的、基于证据的决策的话。这个项目将通过学生与直观地表示化学系统的模型(如碳循环)的互动和操作，探索核心化学主题和计算思维的整合。当学生检查可视的、可运行的模型，进行预测，更改编程代码，然后再次运行该模型时，计算机会向学生提供反馈，要求他们做出解释。预测、解释和测试计算机反馈的过程，再加上结构化的论证过程，支持学生在探索和学习计算和物理世界时像科学家一样思考和行动的能力。弗吉尼亚理工大学和德克萨斯大学奥斯汀分校将研究一种方法，通过在所有学生都参加的背景下提供CT思维：8年级综合科学。有针对性的化学主题将被嵌入到可编辑、可运行的计算模型中，这些模型本身嵌入了专注于基于证据的推理的产生的结构化科学论证的教学方法中。学生将通过与直观表示的模型进行交互来学习化学体系以及平衡和反应速率等关键概念，并通过修改和调整代码以更好地表示化学体系的各个方面来了解CT。四项计算化学任务，包括计算机模型和相关的标准一致的课程，将使用参与性、基于设计的研究技术，与德克萨斯州奥斯汀的四名教师合作，为来自各种社会经济环境的约300名学生提供服务。将开发和验证一个名为辩论驱动的计算思维的课程框架和两个相关的评估工具--计算思维表现评估和计算态度测试。课堂教学活动录像、学生人工制品和计算机使用日志的定量和定性分析将被用来证明这种整合化学和计算的新模式的有效性和广泛的实用性。通过该项目将培养一名博士后和两名研究生。

Computing has become an integral part of everyday practice within modern fields of science, technology, engineering, and math (STEM). As a result, the STEM+Computing Partnerships (STEM+C) program seeks to advance new approaches to, and evidence-based understanding of, the integration of computing in STEM teaching and learning. Computational Thinking (CT) is an intellectual skill rooted in the ability to conceive of meaningful, information-based representations that can be effectively manipulated by a computer. Integrating CT into core science instruction addresses practical constraints in K-12 education, in that there is no room in the curriculum to teach it directly to everyone. But, more importantly, integrating CT into core science provides a synergistic opportunity to deepen instruction in both. STEM education programs that effectively foster development of CT skills as an essential competency are among the most successful in preparing a future STEM workforce that can leverage computational methods to advance basic science and engineering research and design innovative approaches for using data-rich resources to solve complex, societally-relevant problems. Similarly, a science-literate society increasingly needs to appreciate how advances in scientific knowledge are inter-woven with the use of big data, modeling, and simulations, if they are to make informed, evidence-based decisions. This project will explore the integration of core chemistry topics and computational thinking through student interaction with and manipulation of models that visually represent chemical systems, such as the carbon cycle. When a student examines a visual, runnable model, makes a prediction, changes the programming code, and then runs the model again, the computer provides feedback to the student that demands explanation. The process of anticipating, interpreting, and testing the computer's feedback, when coupled with a structured argumentation process, supports a student's abilities to think and act like a scientist as they explore and learn about both the computational and physical world.Virginia Tech and the University of Texas at Austin will investigate a method of broadening access to CT thinking by providing it in a context that all students take: 8th Grade Integrated Science. Targeted chemistry topics will be embedded into editable, runnable computational models that are themselves embedded within a pedagogy of structured scientific argumentation focused on the production of evidence-based reasoning. Students will learn about chemical systems, as well as key concepts such as equilibrium and reaction rates, through interacting with models as they are represented visually and about CT through modifying and adapting the code to better represent aspects of the chemical systems. Four computational chemistry tasks, including computer models and associated standards-aligned curricula, will be developed and refined using participatory, design-based research techniques, in partnership with four Austin, TX teachers serving ~300 students from a variety of socio-economic settings. A curricular framework called Argument Driven Computational Thinking and two associated assessment tools - the Performance Assessment of Computational Thinking and the Computing Attitudes Test - will be developed and validated. Quantitative and qualitative analysis of videotaped classroom instructional activities, student artifacts, and computer-use logs will be used to document the effectiveness and broad utility of this new model for integrating chemistry and computing. A post-doctoral fellow and two graduate students will be trained through this project.