From Data Literacy to Collective Data Stewardship: Technology-Supported Community-Driven Solutions for Urban Youth
From Data Literacy to Collective Data Stewardship: Technology-Supported Community-Driven Solutions for Urban Youth
批准号:
2016982
负责人:
Rosta Farzan
金额:
$59.36万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-10-01 至 2024-09-30
中文摘要
在过去的几十年里,由于制造业工作岗位的外流,美国铁锈地带的城市遭受了经济衰退,并面临着向信息和计算技术产业的重大转变。在许多情况下,由于缺乏工作准备和新劳动力的涌入这些行业,历史上的居民被甩在了后面。该项目的目标是开发技术,通过将大数据分析应用于社区问题来吸引年轻人学习计算技能,以及使年轻人在新经济中取得成功的技能。该项目将使社区成员具备切合实际的学习经验,以培训他们成为社区中的数据托管人,并为他们提供从数据扫盲到数据管理和与技术相关领域的高等教育的途径。该项目将以匹兹堡的两个经济困难和边缘化的社区为目标,吸引被排除在新劳动力市场之外的年轻人,并解决因经济衰退而出现的社区问题。教年轻人使用大数据解决社区问题不仅可以培养计算能力,还可以在参与者中培养更强的公民认同感。通过这个项目开发的技术和课程将被其他社区获取,以便更广泛地实施类似的计划。通过与当地课后计划的合作,该项目将通过关键数据素养和培养对数据和数据驱动技术如何影响他们生活的理解,吸引15至18岁的年轻人发展计算思维。该项目将数据扫盲定义为“对数据的获取、解释、批判性评估、管理、处理和合乎道德的使用”,旨在了解数据扫盲的学习机制,包括个人和集体学习过程以及所需的支持技术。它将涉及开发教育技术,以支持在非正式学习环境中开展数据科学的协作学习,并进行实地研究,以了解以技术为支持、以社区为重点的数据科学学习的进程。为了了解所开发的工具和程序在青年学习收获和公民参与成效方面的成效,该项目将通过记录系统内的行动以及进行前后问卷调查来收集数据。将使用定性和定量相结合的方法来确定数据中的新兴主题,并对数据中的模式进行统计分析。技术进步是一套新颖的协作数据素养工具,为参与提供多个入口点,以适应领域相关、元认知和协作数据素养能力的不同级别。这项研究有助于学习科学理解关键数据素养在社区背景下的地位和边缘化社区个人的现实世界经验如何培养技术知识,促进公民身份的发展,并激励一条通往高等教育的道路。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。
英文摘要
In the past decades, cities across America’s rust belt have suffered economic decline due to the exodus of manufacturing jobs and have faced a significant shift towards Information and Computational Technology industries. In many cases, the historical residents are being left behind, due to lack of job readiness and the influx of a new workforce into these industries. The goal of this project is to develop technology that will engage youth in learning computational skills by applying big data analytics to neighborhood problems as well as skills that will allow youth to succeed in the new economy. The project will equip members of the community in contextually relevant learning experiences to train them as data trustees in their communities, and provide them with a pathway from data literacy to data stewardship and higher education in technology-related fields. The project will target two economically challenged and marginalized neighborhoods of Pittsburgh, engaging youth that have been excluded from the new labor market, and addressing neighborhood issues that arose as part of the economic decline. Teaching youth to use big data to address community problems will not only build computational skills but also foster a stronger civic identity among participants. The technology and curriculum developed through this project will be accessible to other communities for a broader implementation of similar programs.Through partnership with local after-school programs, the project will engage 15 to 18 years-old youth in developing computational thinking through critical data literacy and cultivation of understanding of how data and data-driven technologies influence their lives. Defining data literacy as “access to, interpret, critically assess, manage, handle, and ethical use of data”, the project aims to understand the learning mechanism of data literacy, including individual and collective learning processes as well as required supporting technology. It will involve developing educational technology to support collaborative learning of data science in an informal learning environment as well as conducting field studies to understand the process of technology-supported community-focused learning of data-science. To understand the efficacy of the developed tools and processes on youth’s learning gain and civic engagement efficacy, the project will collect data by logging actions within the system as well as conducting pre- and post- questionnaires. Mixed qualitative and quantitative methods will be used to identify emerging themes in data, and to statistically analyze the patterns in data. The technological advancement is a suite of novel collaborative data literacy tools that provide multiple entry points for participation tailored to different levels of domain-related, metacognitive, and collaborative data literacy competencies. The research contributes to learning sciences understanding of how critical data literacy situated in community context and real world experiences of individuals in marginalized communities can foster technological knowledge, foster the development of a civic identity and motivate a pathway towards higher education.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(1)
专著(0)
科研奖励(0)
会议论文
Proposing a Role Based Framework for Data Literacy
提出基于角色的数据素养框架
DOI:
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发表时间:
2022
期刊:
Proceedings of the 16th International Conference of the Learning Sciences
影响因子:
--
作者:
[Zak Risha, Aditi Mallavarapu]
通讯作者:
Zak Risha, Aditi Mallavarapu
RAPID: Quantifying Hyperlocal Digital Equity: A Path to Supporting Digital Participation
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批准号:2034621
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项目类别:Standard Grant
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资助金额:$19.63万
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财政年份:2020
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负责人:Rosta Farzan
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依托单位:
海外基金