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

这项研究调查了基于块的编程，将日常信息作为传授中学生数据科学技能的工具。科学、技术、工程和数学(STEM)等领域的职业机会越来越需要理解数据的能力。这些技能需要具备数据收集、处理、可视化和分析方面的知识。这个项目探索了培养初中生和高中生数据素养的新方法。新的软件和教育材料将公开提供给学习者和教育工作者使用。针对青少年的研讨会将包括由莫尔黑德天文馆和科学中心运营的青少年科学咖啡馆。通过这项调查，预计该项目将促进有关如何支持年轻人发展以数据为中心的问题解决技能的知识，同时使他们能够使用日常信息进行编程。将创建一个以数据为重点、基于块的可视化编程环境。该环境将使学生能够通过过滤和信息可视化来操作和体验日常数据源。这一编程环境将通过涉及年轻人的形成性研究反复开发。这些研究的定性和定量结果将用于改进系统的设计，以及创造新的知识，解决儿童在参与数据概念和实践时遇到的误解和困难。这个项目的目标是让年轻人发明和开发他们自己的数据工具，而不是只使用它们。预计该奖项将促进对以下方面的科学理解：(1)设计原则和最佳实践，用于创建可视化的、基于块的数据编程工具包，以吸引具有不同兴趣的年轻人参与数据编程；以及(2)年轻人在学习使用数据编程时面临的误解和困难。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。

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.