CRII: CHS: Developing Youth Data Literacies through a Visual Programming Environment

CRII：CHS：通过可视化编程环境培养青少年数据素养

• 批准号: 1948113
• 负责人: Sayamindu Dasgupta
• 金额: $ 17.5万
• 依托单位: University of North Carolina at Chapel Hill
• 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
• 起止时间: 2020-05-15 至 2022-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1948113&HistoricalAwards=false
• 关键词: CRII; CHS; Developing; Youth; Data

This research investigates blocks-based programming with everyday information as a vehicle for teaching secondary school youth data science skills. Professional opportunities in Science, Technology, Engineering, and Mathematics (STEM) and beyond increasingly require abilities for making sense of data. These skills require literacies involving data collection, processing, visualization, and analysis. This project investigates new ways to foster these data literacies in middle and high-school-aged students. New software and educational material will be publicly available for learners and educators to use. Workshops for youth will involve the Teen Science Café, run by the Morehead Planetarium and Science Center. Through this investigation, the project is expected to advance knowledge of how to support youth in developing data-centric problem-solving skills, while enabling them to program with everyday information.A data-focused, visual block-based programming environment will be created. The environment will enable students to manipulate and experience everyday data sources with filtering and information visualization. This programming environment will be developed iteratively through formative research studies involving young people. Qualitative and quantitative results from these studies will be used to both improve the design of the system, as well as to create new knowledge addressing misconceptions and difficulties that kids experience as they engage with data concepts and practices. The goal of this project is to have young people invent and develop their own data tools, rather than only use them. It is expected to advance scientific understanding of (1) design principles and best practices for creating visual, block-based data programming toolkits that can engage youth with diverse interests in programming with data; and (2) misconceptions and difficulties faced by youth while learning to program with data.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.

这项研究通过每天的信息来调查基于块的编程，作为教授中学青年数据科学技能的工具。科学，技术，工程和数学（STEM）的专业机会以及越来越多地要求能够理解数据的能力。这些技能需要涉及数据收集，处理，可视化和分析。该项目调查了在中学和高中生中促进这些数据文学的新方法。新软件和教育材料将公开供学习者和教育者使用。青年研讨会将涉及由莫尔黑德天文馆和科学中心举办的青少年科学咖啡馆。通过这项调查，该项目有望提高有关如何支持年轻人开发以数据为中心的解决问题的技能的知识，同时使他们能够每天的信息进行编程。将创建以数据为中心的，基于视觉块的编程环境。环境将使学生每天通过过滤和信息可视化来操纵和体验数据源。这种编程环境将通过涉及年轻人的形成性研究进行迭代发展。这些研究的定性和定量结果将用于改善系统的设计，并创建新的知识，以解决孩子们在与数据概念和实践互动时遇到的失误和困难。该项目的目的是让年轻人发明和开发自己的数据工具，而不仅仅是使用它们。预计将提高对（1）设计原理和最佳实践的科学理解，以创建基于视觉，基于块的数据编程工具包，这些工具包可以吸引有潜水员在编程中使用数据的青年兴趣； （2）年轻人在学习与数据进行编程时面临的失误和困难。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响标准，通过评估来诚实地获得支持。

项目成果

Dataland: An Informed, Situated, and Critical Approach to Data Literacy

Dataland：一种知情、情境和批判性的数据素养方法

• 发表时间: 2022
• 期刊: General Proceedings of the 2nd Annual Meeting of the International Society of the Learning Sciences 2022
• 作者: Wang, L.;Dasgupta, S.
• 通讯作者: Dasgupta, S.