Building Theories of Scientific Phenomena: Comparing and Integrating Aggregate Pattern-based and Agent-based Computational Approaches

随着计算成为科学、技术、工程和数学(STEM)实践中不可或缺的一部分，STEM计算方案寻求通过将计算思维和计算活动应用于STEM教与学的应用整合来应对计算STEM领域中新出现的挑战。科学教育、研究和标准文件强调需要让学生参与科学家的实践。然而，关于如何让学生参与最核心的科学实践之一--理论建设，人们仍然知之甚少。该项目将调查8年级学生如何参与科学理论建设，包括计算机思维，以及理论建设如何整合到他们的科学课程中。科学家有很多方法来构建理论。在某些情况下，它们从数据开始并抽象出一种关系，以便用数学模型(即聚合模式方法)更准确地描述它。在其他情况下，他们假设一种现象的机制，从对一个系统的假设开始(例如，它的要素及其相互作用)，并建立一个计算模型，当运行时，产生可以探索的结果(即，个别机制方法)。目前还没有任何教育研究试图确定这两种方法的共同点和不同点。该项目将调查每种理论建设方法的学习机会，并利用这些结果创建整合两种方法的课程单元。该项目将为教育研究基地做出贡献，并传播项目研究成果，供科学教师、课程开发人员和教学教练使用。研究旨在了解1)学生产生理论的特点；2)他们产生理论的过程；3)学生学习结果的特点。这些问题是通过基于实验室的研究来解决的，这些研究通过引导学生阐明数据中看到的聚集级别的模式或开发基于代理的计算模型来表示模式背后的机制，从而向学生介绍现象。调查结果将指导课程单元的设计，这些单元将在第三年通过以设计为基础的研究进行测试。这些发现将阐明如何将这两种方法结合起来，帮助学生了解科学现象和理论构建过程。这项研究还将深入了解不同表征的产生如何提供不同的学习途径。研究的产品将为课程教材和软件的开发提供参考。本研究为理论建构教学的设计和实施提供了一般原则，具有一定的实用价值。所生产的软件将扩展广泛使用的NetLogo和NetTango平台，以促进构建理论计算模型。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

As computing has become integral to the practice of science, technology, engineering and mathematics (STEM), the STEM+Computing program seeks to address emerging challenges in computational STEM areas through the applied integration of computational thinking and computing activities within STEM teaching and learning in early childhood education through high school (preK-12). Science education research and standards documents emphasize the need for engaging students in the practices of scientists. Yet still little is known about how to engage students in one of the most central practices of science, theory building. The project will investigate how 8th grade students can engage in scientific theory building, including computatinal thinking, and how theory building can be integrated into their science curriculum. There are many ways scientists approach building theory. In some cases, they begin with data and abstract a relationship in order to more precisely describe it in terms of a mathematical model (i.e., aggregate pattern approach). In other cases, they posit the mechanism for a phenomenon, beginning with assumptions about a system (e.g., its elements and their interactions) and build a computational model that, when run, produces outcomes that can be explored (i.e., individual mechanism approach). No educational research studies have yet sought to characterize the commonalities and differences of the two approaches. The project will investigate the learning opportunities of each approach to theory building and use these results to create curricular units that integrate the two approaches. The project will contribute to the educational research base and disseminate project research findings for use by science teachers, curriculum developers, and instructional coaches.The research aims to understand the character of 1) the theories the students produce; 2) the processes by which they produce their theories; and 3) the characteristics of student learning that result. These questions are addressed through lab-based studies that introduce students to phenomena by guiding them to either articulate the aggregate-level pattern seen in data or develop agent-based computational models that represent the mechanism behind the pattern. Findings will inform the design of curricular units that will be tested through design-based research in the third year. These findings will illuminate how the two approaches can be integrated to help students learn about both scientific phenomena and theory-building processes. The research will also extend insight into how the production of different representations affords different learning pathways. Products of the study will inform the development of curricular materials and software. The research will be of practical value by informing general principles for designing and conducting theory-building instruction. The software produced will extend the widely used NetLogo and NetTango platforms to facilitate building theoretical computational models.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.