Collaborative Research: New Pathways into Data Science: Extending the Scratch Programming Language to Enable Youth to Analyze and Visualize Their Own Learning
协作研究:数据科学的新途径:扩展 Scratch 编程语言,使青少年能够分析和可视化自己的学习
基本信息
- 批准号:1417952
- 负责人:
- 金额:$ 30.89万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2014
- 资助国家:美国
- 起止时间:2014-09-01 至 2016-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This REAL project arises from the 2013 solicitation on Data-intensive Research to Improve Teaching and Learning. The intention of that effort is to bring together researchers from across disciplines to foster novel, transformative, multidisciplinary approaches to using the data in large education-related data sets to create actionable knowledge for improving STEM teaching and learning environments in the medium term and to revolutionize learning in the longer term. This project addresses the issue of how to represent and communicate data to young people so that they can track their learning and weaknesses and take advantage of what they learn through that tracking. The project team aims to address this challenge by giving young people (middle schoolers) the tools and support to create, manipulate, analyze, and share representations of their own understanding, capabilities, and participation within the Scratch environment. Scratch is a programming language and online community in which youngsters (mostly middle schoolers) engage in programming together, sometimes to make scientific models and sometimes to express themselves artistically using sophisticated computer algorithms. Scratch community participants are often interested in keeping track of what they are learning, so this population is a good one for exploring ways of helping young people make sense of data that records their participation and learning. The team will extend the Scratch programming language with facilities for manipulating, analyzing, and representing such data, and Scratch participants will be challenged to make sense of their learning and participation data and helped to use the new facilities to do write programs to carry out such interpretation. Scratch participants will become visualizers of their participation patterns and learning trajectories; research will address how such data explorations influence their learning trajectories. Scratch and its community are the place for the proposed investigations, but what is learned will apply far more broadly to construction of tools for allowing learners to understand their participation and learning across a broad range of environments.This project addresses the sixth challenge in the program solicitation: how can information extracted from large datasets be represented and communicated to maximize its usefulness in real-time educational stings, and what delivery mechanisms are right for that? The PIs go right to the learners; rather than looking for delivery mechanisms for communicating the data representations, they give young people tools and support to create manipulate, analyze, and share those representations, bringing together approaches to quantitative evidence-based learning analytics with the constructionist tradition of learning through design experiences. In addition to helping us learn about how to help youngsters analyze data about their perforance and self-assess, the PIs expect that their endeavor will help us better learn how to help young people become data analyzers, an important part of computational thinking. Learners will, in the process of engaging with data representing their development and participation, interact with visualizations, model and troubleshoot data sets, and search for patterns in large data sets. In addition, the tools being developed as part of this project will be applicable for analysis of other types of data sets. The results that will transfer beyond Scratch and the Scratch community, are (1) the kinds of tools that make such analysis possible for youngsters, (2) the kinds of challenges that will get youngsters interested in doing such analyses, (3) the kinds of data youngsters can handle, and (4) the kinds of scaffolding and coaching youngsters need to make sense of that data.
这个 REAL 项目源于 2013 年关于改善教学的数据密集型研究的征集。这项工作的目的是汇集跨学科的研究人员,培育新颖的、变革性的、多学科的方法,利用大型教育相关数据集中的数据来创造可操作的知识,以在中期改善 STEM 教学环境,并在长期内彻底改变学习。该项目解决了如何向年轻人展示和交流数据的问题,以便他们能够跟踪他们的学习和弱点,并利用他们通过跟踪学到的东西。项目团队旨在通过为年轻人(中学生)提供工具和支持来应对这一挑战,以在 Scratch 环境中创建、操作、分析和分享他们自己的理解、能力和参与的表现形式。 Scratch 是一种编程语言和在线社区,青少年(主要是中学生)可以在其中一起编程,有时制作科学模型,有时使用复杂的计算机算法艺术地表达自己。 Scratch 社区参与者通常有兴趣跟踪他们正在学习的内容,因此这一群体非常适合探索帮助年轻人理解记录他们的参与和学习的数据的方法。该团队将扩展 Scratch 编程语言,提供用于操作、分析和表示此类数据的工具,Scratch 参与者将面临理解他们的学习和参与数据的挑战,并帮助使用新工具编写程序来执行此类解释。 Scratch 参与者将成为他们的参与模式和学习轨迹的可视化者;研究将解决此类数据探索如何影响他们的学习轨迹。 Scratch 及其社区是拟议调查的场所,但所学到的知识将更广泛地应用于构建工具,让学习者了解他们在广泛环境中的参与和学习。该项目解决了项目征集中的第六个挑战:如何表示和传达从大型数据集中提取的信息,以最大限度地提高其在实时教育中的有用性,以及哪些交付机制适合这一点? PI 直接传达给学习者;他们不是寻找传达数据表示的传递机制,而是为年轻人提供工具和支持来创建操作、分析和共享这些表示,将基于证据的定量学习分析方法与通过设计经验学习的建构主义传统结合起来。除了帮助我们了解如何帮助年轻人分析有关其表现和自我评估的数据外,PI 还希望他们的努力将帮助我们更好地学习如何帮助年轻人成为数据分析员,这是计算思维的重要组成部分。学习者将在处理代表其发展和参与的数据的过程中,与可视化进行交互,对数据集进行建模和故障排除,并在大型数据集中搜索模式。此外,作为该项目的一部分正在开发的工具将适用于其他类型的数据集的分析。将转移到 Scratch 和 Scratch 社区之外的结果是:(1) 使此类分析成为可能的工具类型,(2) 使孩子们对进行此类分析感兴趣的挑战类型,(3) 孩子们可以处理的数据类型,以及 (4) 孩子们需要什么样的脚手架和指导来理解这些数据。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Mitchel Resnick其他文献
Thinking Like a Tree (and Other Forms of Ecological Thinking)
- DOI:
10.1023/a:1025632719774 - 发表时间:
2003-09-01 - 期刊:
- 影响因子:3.500
- 作者:
Mitchel Resnick - 通讯作者:
Mitchel Resnick
Mitchel Resnick的其他文献
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{{ truncateString('Mitchel Resnick', 18)}}的其他基金
INDP: Collaborative Research: Coding for All: Interest-Driven Trajectories to Computational Fluency
INDP:协作研究:全民编码:兴趣驱动的计算流畅性轨迹
- 批准号:
1348911 - 财政年份:2014
- 资助金额:
$ 30.89万 - 项目类别:
Standard Grant
Collaborative Research: ScratchJr: Computer Programming in Early Childhood Education as a Pathway to Academic Readiness and Success
合作研究:ScratchJr:幼儿教育中的计算机编程作为学术准备和成功的途径
- 批准号:
1118682 - 财政年份:2011
- 资助金额:
$ 30.89万 - 项目类别:
Standard Grant
ScratchEd: Working with Teachers to Develop Design-based Approaches to the Cultivation of Computational Thinking
ScratchEd:与教师合作开发基于设计的方法来培养计算思维
- 批准号:
1019396 - 财政年份:2010
- 资助金额:
$ 30.89万 - 项目类别:
Standard Grant
CDI-Type II: Collaborative Research: Preparing the Next Generation of Computational Thinkers: Transforming Learning and Education Through Cooperation in Decentralized Networks
CDI-类型 II:协作研究:培养下一代计算思想家:通过去中心化网络中的合作改变学习和教育
- 批准号:
1027848 - 财政年份:2010
- 资助金额:
$ 30.89万 - 项目类别:
Standard Grant
Major: Scratch 2.0: Cultivating Creativity and Collaboration in the Cloud
专业:Scratch 2.0:在云端培养创造力和协作
- 批准号:
1002713 - 财政年份:2010
- 资助金额:
$ 30.89万 - 项目类别:
Standard Grant
Broadening Participation at the Scratch@MIT Conference
扩大 Scratch@MIT 会议的参与范围
- 批准号:
1041290 - 财政年份:2010
- 资助金额:
$ 30.89万 - 项目类别:
Standard Grant
ITR: A Networked, Media-Rich Programming Environment to Enhance Informal Learning and Technological Fluency at Community Technology Centers
ITR:一个网络化、媒体丰富的编程环境,可增强社区技术中心的非正式学习和技术流畅性
- 批准号:
0325828 - 财政年份:2003
- 资助金额:
$ 30.89万 - 项目类别:
Continuing Grant
The PIE Network: Promoting Science Inquiry and Engineering through Playful Invention and Exploration with New Digital Technologies
PIE 网络:通过新数字技术的有趣发明和探索促进科学探究和工程
- 批准号:
0087813 - 财政年份:2001
- 资助金额:
$ 30.89万 - 项目类别:
Continuing Grant
CISE/EHR/ENG/MPS Collaborative Research on Learning Technologies: Beyond Black Boxes: Bring Transparency and Aesthetics Back to Scientific Instruments
CISE/EHR/ENG/MPS 学习技术合作研究:超越黑匣子:让科学仪器回归透明和美观
- 批准号:
9616444 - 财政年份:1997
- 资助金额:
$ 30.89万 - 项目类别:
Standard Grant
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