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

计算已经成为现代科学、技术、工程和数学（STEM）领域日常实践中不可或缺的一部分。因此，STEM+计算伙伴关系（STEM+C）计划寻求推进新的方法，并以证据为基础的理解，将计算整合到STEM教学和学习中。计算思维（computer Thinking， CT）是一种智力技能，根植于构思有意义的、基于信息的表征的能力，这些表征可以被计算机有效地操纵。将CT整合到核心科学教学中，解决了K-12教育的实际限制，因为课程中没有空间直接向每个人教授CT。但是，更重要的是，将CT整合到核心科学中提供了深化这两方面教学的协同机会。STEM教育项目有效地促进了计算机计算机技能的发展，将其作为一种基本能力，在培养未来的STEM劳动力方面是最成功的，这些劳动力可以利用计算方法推进基础科学和工程研究，并设计创新方法，利用丰富的数据资源来解决复杂的社会相关问题。同样，一个具有科学素养的社会越来越需要认识到，如果他们要做出明智的、基于证据的决策，科学知识的进步是如何与大数据、建模和模拟的使用交织在一起的。该项目将探索核心化学主题与计算思维的整合，通过学生与可视化表示化学系统（如碳循环）的模型的互动和操作。当学生检查一个可视化的、可运行的模型，做出预测，修改编程代码，然后再次运行模型时，计算机向学生提供需要解释的反馈。预测、解释和测试计算机反馈的过程，加上结构化的论证过程，支持学生在探索和学习计算世界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，通过提供所有学生都参加的情境来扩大CT思维的范围：八年级综合科学。目标化学主题将嵌入到可编辑的、可运行的计算模型中，这些计算模型本身嵌入在结构化的科学论证教学法中，侧重于循证推理的产生。学生将学习化学系统，以及关键的概念，如平衡和反应速率，通过与模型互动，因为他们是可视化的，并通过修改和调整代码，以更好地表示化学系统的各个方面的CT。四项计算化学任务，包括计算机模型和相关的标准课程，将与德克萨斯州奥斯汀的四位教师合作，使用参与式的、基于设计的研究技术，为来自各种社会经济背景的约300名学生提供服务。一个名为“论证驱动计算思维”的课程框架和两个相关的评估工具——“计算思维绩效评估”和“计算态度测试”——将被开发和验证。对课堂教学活动录像、学生人工制品和计算机使用日志的定量和定性分析将用于证明这种整合化学和计算的新模型的有效性和广泛用途。本项目将培养1名博士后和2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.