Computational Thinking for Science: Positioning coding as a tool for doing science

IF 3.6 1区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH Journal of Research in Science Teaching Pub Date : 2023-10-04 DOI:10.1002/tea.21907
Ari Krakowski, Eric Greenwald, Natalie Roman, Christina Morales, Suzanna Loper
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Abstract

The role of computation in science is ever-expanding and is enabling scientists to investigate complex phenomena in more powerful ways and tackle previously intractable problems. The growing role of computation has prompted calls to integrate computational thinking (CT) into science instruction in order to more authentically mirror contemporary science practice and to support inclusive engagement in science pathways. In this multimethods study, we present evidence for the Computational Thinking for Science (CT+S) instructional model designed to support broader participation in science, technology, engineering, and mathematics (STEM) pathways by (1) providing opportunities for students to learn CT within the regular school day, in core science classrooms; and (2) by reframing coding as a tool for developing solutions to compelling real-world problems. We present core pedagogical strategies employed in the CT+S instructional model and describe its implementation into two 10-lesson instructional units for middle-school science classrooms. In the first unit, students create computational models of a coral reef ecosystem. In the second unit, students write code to create, analyze, and interpret data visualizations using a large air quality dataset from the United States Environmental Protection Agency to understand, communicate, and evaluate solutions for air quality concerns. In our investigation of the model's implementation through these two units, we found that participating students demonstrated statistically significant advancements in CT, competency beliefs for computation in STEM, and value assigned to computation in STEM. We also examine evidence for how the CT+S model's core pedagogical strategies may be contributing to observed outcomes. We discuss the implications of these findings and propose a testable theory of action for the model that can serve future researchers, evaluators, educators, and instructional designers.

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科学计算思维:将编码定位为科学工具
计算在科学中的作用不断扩大,使科学家能够以更强大的方式研究复杂的现象,解决以前难以解决的问题。计算的作用越来越大,促使人们呼吁将计算思维(CT)融入科学教学,以便更真实地反映当代科学实践,支持全纳参与科学学习。在这项多方法研究中,我们提出了科学计算思维(CT+S)教学模式的证据,该模式旨在通过以下方式支持更广泛地参与科学、技术、工程和数学(STEM)课程:(1)在核心科学课堂上,为学生提供在正常上课时间内学习计算思维的机会;(2)将编码重新定义为一种工具,用于开发解决现实世界中令人信服的问题的方案。我们介绍了 CT+S 教学模式所采用的核心教学策略,并描述了其在初中科学课堂两个 10 课时教学单元中的实施情况。在第一个单元中,学生创建珊瑚礁生态系统的计算模型。在第二个单元中,学生编写代码,使用美国环境保护局提供的大型空气质量数据集创建、分析和解释数据可视化,以了解、交流和评估空气质量问题的解决方案。在通过这两个单元对该模式实施情况的调查中,我们发现参与调查的学生在 CT、STEM 中计算的能力信念以及 STEM 中计算的价值分配方面都取得了统计意义上的显著进步。我们还研究了 CT+S 模式的核心教学策略如何促进观察结果的证据。我们讨论了这些发现的意义,并为该模式提出了一个可检验的行动理论,以服务于未来的研究人员、评估人员、教育工作者和教学设计人员。
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来源期刊
Journal of Research in Science Teaching
Journal of Research in Science Teaching EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
8.80
自引率
19.60%
发文量
96
期刊介绍: Journal of Research in Science Teaching, the official journal of NARST: A Worldwide Organization for Improving Science Teaching and Learning Through Research, publishes reports for science education researchers and practitioners on issues of science teaching and learning and science education policy. Scholarly manuscripts within the domain of the Journal of Research in Science Teaching include, but are not limited to, investigations employing qualitative, ethnographic, historical, survey, philosophical, case study research, quantitative, experimental, quasi-experimental, data mining, and data analytics approaches; position papers; policy perspectives; critical reviews of the literature; and comments and criticism.
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