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CSforAll: Making CT: Integrating Computational Thinking into Elementary Classrooms

CSforAll: Making CT: Integrating Computational Thinking into Elementary Classrooms
CSforAll:制作 CT:将计算思维融入基础课堂
批准号:
1923503
负责人:
Jennifer Albert
金额:
$29.85万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-01 至 2023-08-31

项目摘要

项目成果

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中文摘要
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英文摘要
The goal of this project is to develop and investigate a model to support P-5 teachers in implementing interdisciplinary, computational thinking-integrated lessons. The strategy is to employ a model of professional development that was previously developed to support elementary teachers to integrate computational thinking into their teaching of school subjects. This study turns attention to the systemic support for broadening and sustaining this integration of computational thinking through development of a research practice partnership between the Citadel and Charleston Progressive Academy, an elementary school serving a historically marginalized urban community. The study analyzes how teachers develop expertise in integrating computational thinking activities and how the broader school system provides supports for realizing and sustaining this development. Ultimately, the findings serve as a foundation for design of scalable elementary teacher professional development and ongoing support for computational thinking integration.Over the two years of the project, at least 10 teachers will engage in reflective PD sessions held throughout the academic year and summer. In these, teachers will explore, co-design, and implement activities that integrate computational thinking into their existing content area standards and curricula. The computational thinking activities, which will include standards-based lesson plans and resources, offer both plugged and unplugged components, so that students and teachers have opportunities to understand the conceptual underpinnings of computational thinking with and without computers. Surrounding this effort is support from a broader set of stakeholders, including researchers and school administrators, that facilitate the project's efforts and provide formative feedback. Over the two years of this study, cycles of design and analysis are used to refine conjectures for the design of computational thinking lessons and related teacher professional development from this broader community's perspective. The study provides a set of empirically-tested design conjectures from which others can develop computational thinking lessons and professional development specifically tailored to other state, district, or school contexts. Research on this project is studying the trajectories of teacher learning, as they increase their ability to integrate computational thinking into their teaching of school subjects. In addition, analyses include investigations of the research-practice partnership itself, focusing on how this partnership works with school-based stakeholders to best support teachers toward its goals. This project is funded by the CS for All program.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.
期刊论文(3)
专著(0)
科研奖励(0)
会议论文
DOI: --
发表时间: 2022
期刊: Literacy Research Association
影响因子: --
作者: [Jocius, R.]
通讯作者: Jocius, R.
DOI: 10.1080/19415257.2023.2228813
发表时间: 2023
期刊: Professional Development in Education
影响因子: 2.1
作者: [Jocius, Robin, Joswick, Candace, Albert, Jennifer, Joshi, Deepti, Blanton, Melanie]
通讯作者: Blanton, Melanie
DOI: 10.58680/la202332307
发表时间: 2023
期刊: Language Arts
影响因子: --
作者: [Blanton, Melanie, Jocius, Robin, Albert, Jennifer, Joshi, Deepti, Andrews, Ashley]
通讯作者: Andrews, Ashley
Collaborative Research: Unpacking Computational Thinking for Elementary Teachers and Learners
Learning to Lead (L2L): Building STEM Teacher Leaders that Broaden Participation in High-Need Schools
Collaborative Research: Integrating computing in STEM: Designing, developing, and investigating a team-based professional development model for middle- and high-school teachers
DCL: EAGER: MAKER: Determining the Efficacy of Maker Activities by Navigating Discourse (DEMAND)
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis