Modeling and measuring critical data literacies in informal learning environments

社会对数字技术的依赖导致了大量数据被记录、分类和分析。在提高人类效率和生活质量的同时，数据分析也会重现不平等，并进一步边缘化那些来自非主流人群的人，包括妇女、有色人种和生活在贫困中的人。这个为期两年的STEM教育研究能力建设个人调查员发展项目通过为中学生开发一个审查数字技术的社会和伦理维度的数据科学教育计划来解决这个问题。通过让100多名顾问、家长、学生和研究人员作为数据科学教育项目的联合设计师，在一个基于课外社区的项目中，该项目有可能教育计算机教育领域的一系列利益相关者。此外，它还有可能扩大对STEM的参与，为STEM中传统上代表性不足的青年提供丰富的、与文化相关的经验，这些经验可能会激励他们追求STEM专业和职业。具体的项目研究目标是：(1)在与数字技术有关的社会、伦理和政治问题的背景下衡量和示范青年的数据科学知识和做法；以及(2)衡量青年的赋权意识，以在其社区中以伦理方式使用数字技术方面的变革。该项目整合了数据科学教育研究和社会文化学习理论，以建立对社会/伦理/政治问题背景下数据科学学习性质的新的理论理解。这种方法可以促进对中学年龄段青年如何以在他们自己的文化和更广泛的STEM社区中受到重视的方式参与数据实践的了解和理解。该项目还支持发展关键数据科学学习理论的长期目标，以及如何让年轻人参与社区计划，以促进道德、文化响应和关键的STEM学习机会。专业发展目标是培养首席调查员对参与式设计的理解，为非正式学习环境中的青年设计设计的能力，以及获得定量人种学工具和方法的能力。该项目由EHR核心研究：STEM教育研究中的能力建设(ECR：BCSER)比赛支持，该比赛旨在培养个人在STEM学习和学习环境中开展高质量基础STEM教育研究的能力，扩大对STEM领域的参与，以及STEM劳动力发展。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。

Society’s reliance on digital technologies has resulted in enormous amounts of data being recorded, sorted, and analyzed. While improving human efficiency and life quality, data analytics can also reproduce inequities and further marginalize those from non-dominant populations, including women, people of color, and those who live in poverty. This two-year Building Capacity in STEM Education Research Individual Investigator Development project addresses this issue by developing a data science education program for middle school students that examines the social and ethical dimensions of digital technologies. By engaging over 100 counselors, parents, students, and researchers as co-designers of the data science education program at an after-school community-based program, the project has potential to educate a range of stakeholders in computing education. Moreover, it has potential to broaden participation in STEM by providing youth who are traditionally underrepresented in STEM with rich and culturally relevant experiences that may motivate them to pursue STEM majors and careers.Specific project research objectives are to: (1) measure and model youth’s data science knowledge and practices in the context of social, ethical, and political issues related to digital technologies; and (2) measure youth’s sense of empowerment to enact change in their communities in terms of the ethical use of digital technologies. The project integrates data science education research and sociocultural learning theories to build new theoretical understandings about the nature of data science learning in the context of social/ethical/political issues. This approach can advance knowledge and understanding of how middle school aged youth engage in data practices in ways that are valued within their own cultures and within broader STEM communities. The project also supports the long-term goal of developing theories of critical data science learning and how to engage youth in community programs that promote ethical, culturally responsive, and critical STEM learning opportunities. The professional development objectives are to develop the Principal Investigator’s understanding of participatory design, ability to design for youth in informal learning environments and access to quantitative ethnography tools and methods.The project is supported through the EHR Core Research: Building Capacity in STEM Education Research (ECR: BCSER) competition that is designed to build individuals’ capacity to carry out high quality fundamental STEM education research in STEM learning and learning environments, broadening participation in STEM fields, and STEM workforce development.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.