From Access to Sustainability: Investigating Ways to Foster Sustainable Use of Computational Modeling in K-12 Science Classrooms

建模是一项核心的科学活动，在该活动中，以视觉或计算机程序的形式表示难以观察的现象。研究表明，持续的建模经验有助于对科学实践的深入理解、学习和参与。计算建模是集成计算和科学学习的一种很有前途的方法。然而，由于学生需要时间成为熟练的建模人员，需要更好地将计算建模与其他科学实践相结合，以及教师需要在使用这些建模工具时体验代理等困难，计算建模在科学课堂上的持续时间并未得到广泛采用。这个设计与开发项目通过两种方式调查如何支持中学课堂持续参与计算建模：1)设计和开发一个可访问的建模工具包，并附带主题链接的课程单元；以及，2)研究这个工具包和课程如何使学生成为成熟的模型师，并将建模与其他科学实践(如物理实验和论证)相结合。该项目将有助于围绕如何支持学生和教师将计算建模与有价值的科学实践结合在一起，持续地在课堂上进行讨论。该项目将与六名六年级和七年级的教师和大约400名学生合作三年，通过以设计为基础的研究的迭代周期，该项目将为六年级和七年级的学生设计一个计算建模工具和六个课程单元。该团队将与两名教师共同设计人员密切合作，设计和开发六个课程单元中的每个单元。我们的目标是调查：1)当学生从使用现象级原语转向拆开和修改这些原语以进行扩展研究时，他们是如何成为复杂的建模人员的；2)关于计算建模的课堂规范是如何随着时间的推移而发展的。具体地说，学生模型如何成为课堂反思的对象，以及学生如何将建模与其他实践相结合，如解释和论证；3)物理实验数据如何支持学生构建和改进模型；以及4)持续参与如何支持学生的概念学习和使用计算工具学习建模。该团队将收集和分析视频和书面数据，以及日志文件和前后测试，以检查学生和教师社区如何将计算建模作为科学学习中的一项整体实践。对于视频和文本分析，团队将使用定性编码来检测活动之前、期间和之后的模式。对于软件日志文件的检查，该项目将使用学习分析技术，例如对学生的行动顺序进行分类和分类。最后，该团队还将对内容和元建模技能进行前后测试，并使用标准的统计测试来分析结果。该项目由教育和人力资源局的NSF发现研究PreK-12(DRK-12)计划支持。DRK-12旨在通过研究和开发创新的资源、模式和工具，显著提高K-12学前班学生和教师的科学、技术、工程和数学(STEM)的学习和教学。DRK-12计划中的项目建立在STEM教育的基础研究和先前的研究和开发工作的基础上，为拟议的项目提供了理论和经验上的证明。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。

Modeling is a core scientific activity in which a difficult-to-observe phenomenon is represented, e.g., visually or in a computer program. Research has shown that sustained experience with modeling contributes to sophisticated understanding, learning, and engagement of scientific practices. Computational modeling is a promising way to integrate computation and science learning. Yet computational modeling is not widely adopted in science classrooms over sustained periods of time because of difficulties such as the time required for students to become adept modelers, the need to better integrate computational modeling with other scientific practices, and the need for teachers to experience agency in using these modeling tools. This Design and Development project investigates how to support sustained engagement in computational modeling in middle school classrooms in two ways: 1) Design and develop an accessible modeling toolkit and accompanying thematically linked curricular units; and, 2) Examine how this toolkit and curriculum enable students to become sophisticated modelers and integrate modeling with other scientific practices such as physical experimentation and argumentation. The project will contribute to the conversation around how to support students and teachers to incorporate computational modeling together with valued scientific practices into their classrooms for sustained periods. For three years, the project will work with six sixth and seventh grade teachers and approximately 400 students.Through iterative cycles of design-based research, the project will design a computational modeling tool and six curricular units for sixth and seventh-grade students. The team will work closely with two teacher co-designers to design and develop each of the six curricular units. The goal is to investigate: 1) How students become sophisticated modelers as they shift from using phenomenon-level primitives to unpacking and modifying these primitives for extended investigations; 2) How classroom norms around computational modeling develop over time. Specifically, how do student models become objects for classroom reflection and how students integrate modeling into other practices such as explanation and argumentation; 3) How data from physical experiments support students in constructing and refining models; and, 4) How sustained engagement supports students’ conceptual learning and learning to model using computing tools. The team will collect and analyze video and written data, as well as log files and pre/posttests, to examine how communities of students and teachers adopt computational modeling as an integral practice in science learning. For video and text analysis, the team will use qualitative coding to detect patterns before, during, and after the activities. For the examination of logfiles from the software, the project will use learning analytics techniques such as the classification and clustering of students’ sequences of actions. Finally, the team will also conduct pre/post-tests on both content and meta-modeling skills, analyzing the results with standard statistical tests.This project is supported by NSF's Discovery Research PreK-12 (DRK-12) program, in the Directorate for Education & Human Resources. DRK-12 seeks to significantly enhance the learning and teaching of science, technology, engineering and mathematics (STEM) by preK-12 students and teachers through research and development of innovative resources, models and tools. Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for proposed projects.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.