Integrated Science Practices Enhanced by Computational Thinking (InSPECT)

计算思维增强综合科学实践 (InSPECT)

• 批准号: 1640054
• 负责人: Sherry Hsi
• 金额: $ 249.72万
• 依托单位: Concord Consortium
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-10-01 至 2021-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1640054&HistoricalAwards=false
• 关键词: Integrated; Science; Practices; Enhanced; Computational

This project is funded by the STEM+Computing Partnership (STEM+C) program, which seeks to advance new approaches to, and evidence-based understanding of, the integration of computing in STEM teaching and learning. This project will contribute to that effort by developing new curriculum units for high school biology courses that integrate computational thinking within biology. The units will feature inquiry-oriented investigations that will require students to design procedures using a variety of computer-controlled sensors, actuators, video-capture devices, and other technologies to solve open-ended problems. Students will use a simplified visual programming language, called Dataflow, to automate experimental procedures, collect and visualize data, and wirelessly link to data sharing devices. To use these real-time resources effectively, students will need to link the causal (cause and effect) thinking of the natural sciences to the computational thinking skills of computer science. The project will develop 12 curriculum units comprising 6 background units, 3 highly structured set-piece experiments, and 3 open-ended projects. Sets of two background units, 1 set-piece experiment, and one open-ended project will allow students to progress through development of foundational knowledge and experimental skills before taking on the challenge of an open-ended project. The outcomes of this project have high potential to advance classroom practices in science by identifying ways of using computers and computational thinking to engage students more deeply in the processes and reasoning of scientific inquiry.The project will conduct design-based research, using the first two project years to develop and validate a pedagogical model of integration between science and computational thinking practices and related activities. In year three, the project will undertake a pilot implementation to test the feasibility of the project's innovations in the biology classes taught by 26 teachers in diverse schools. The project will provide teachers with teaching resources, technology, and professional development designed to enable their students to undertake two science investigations requiring a total of four to six weeks of classes. A mixed-methods research strategy will be employed both to characterize and estimate student gains in applying computational thinking, carrying out science practices, and understanding core biology content knowledge related to ecosystems. Data will be gathered from classroom observations, pretests and posttests, embedded assessments in activities, student screencast reports, interviews with teachers and students, and log data automatically collected by learning software. This variety of data sources will be triangulated to validate research findings from multiple perspectives. Three questions guide the research: A) To what extent and under what conditions are students able to use the project's computational resources to undertake authentic scientific investigations? B) When students are engaged in science experimentation made possible by the resources, approach, and designed tools, what learning gains will be observed in student abilities to perform science practices, exercise computational thinking, and understand biology concepts? What factors are associated with differences in the gains, if any? and C) What kinds of background materials and assistance do teachers require for effective enactments of the intended curriculum? Specifically, how important is teacher background and experience with computers to support student use of technology-enabled experimentation? What was the impact of various kinds of teacher supports on the quality of the classroom enactments.

该项目由STEM+Computing Partnership（STEM+C）计划资助，该计划旨在推进STEM教学和学习中计算整合的新方法和基于证据的理解。该项目将通过为高中生物课程开发新的课程单元，将计算思维融入生物学，为这一努力做出贡献。这些单元将以探究为导向的调查为特色，要求学生使用各种计算机控制的传感器，执行器，视频捕捉设备和其他技术来设计程序，以解决开放式问题。学生将使用简化的可视化编程语言，称为数据流，自动化实验程序，收集和可视化数据，并无线连接到数据共享设备。为了有效地使用这些实时资源，学生需要将自然科学的因果（因果）思维与计算机科学的计算思维技能联系起来。该项目将开发12个课程单元，其中包括6个背景单元，3个高度结构化的实验和3个开放式项目。两个背景单元，一个集合实验和一个开放式项目的集合将允许学生在接受开放式项目的挑战之前通过基础知识和实验技能的发展取得进展。 该项目的成果具有很大的潜力，通过确定使用计算机和计算思维的方法，使学生更深入地参与科学探究的过程和推理，来推进科学课堂实践。该项目将进行基于设计的研究，利用前两个项目年开发和验证科学与计算思维实践和相关活动相结合的教学模式。在第三年，该项目将进行试点实施，以测试该项目在不同学校的26名教师教授的生物课上的创新的可行性。该项目将为教师提供教学资源、技术和专业发展，使他们的学生能够进行两项科学调查，总共需要四到六周的课程。将采用混合方法研究策略来表征和估计学生在应用计算思维，进行科学实践和理解与生态系统相关的核心生物学内容知识方面的收益。数据将从课堂观察、前测和后测、活动中的嵌入式评估、学生截屏报告、教师和学生访谈以及学习软件自动收集的日志数据中收集。将对各种数据来源进行三角分析，以从多个角度验证研究结果。三个问题指导研究：A）在什么程度上和条件下，学生能够使用项目的计算资源进行真实的科学调查？B）当学生通过资源、方法和设计的工具进行科学实验时，在学生进行科学实践、锻炼计算思维和理解生物学概念的能力方面会观察到什么样的学习收获？哪些因素与收益的差异有关？C）教师需要什么样的背景材料和帮助来有效地制定预期的课程？具体来说，教师的计算机背景和经验对支持学生使用技术实验有多重要？不同类型的教师支持对课堂教学质量的影响是什么？

项目成果

Student Epistemic Agency and Coherence-seeking through Laboratory Experiments

学生认知能动性和通过实验室实验寻求连贯性

• DOI: 10.22318/icls2021.689
• 发表时间: 2021
• 期刊: Proceedings of the 15th International Conference of the Learning Sciences - ICLS 2021
• 作者: Hardy, Lisa;Dixon, Colin
• 通讯作者: Dixon, Colin

Sensors and Spinach: Increasing Student Agency in Biology Class

传感器和菠菜：提高生物课上学生的能动性

• 发表时间: 2020
• 期刊: @Concord
• 作者: Van Doren, Seth

Computational Tinkering in Science: Designing Space for Computational Participation in High School Biology

科学中的计算修补：为高中生物学中的计算参与设计空间

• DOI: 10.22318/icls2020.154
• 发表时间: 2020
• 期刊: 14th International Conference of the Learning Sciences (ICLS
• 作者: Dixon, Colin;Hardy, Lisa;Hsi, Sherry;Van Doren, Seth
• 通讯作者: Van Doren, Seth

Science Thinking for Tomorrow Today

今天的科学思考明天

• 发表时间: 2017
• 期刊: @Concord
• 作者: Hsi, S.

Probeware for the Modern Era: IoT Dataflow System Design for Secondary Classrooms

现代时代的 Probeware：中学教室的物联网数据流系统设计

• DOI: 10.1109/tlt.2021.3061040
• 发表时间: 2021
• 期刊: IEEE Transactions on Learning Technologies
• 影响因子: 3.7
• 作者: Bondaryk, Leslie G.;Hsi, Sherry;Van Doren, Seth
• 通讯作者: Van Doren, Seth