Modeling and measuring critical data literacies in informal learning environments

在非正式学习环境中建模和测量关键数据素养

• 批准号: 2024965
• 负责人: Golnaz Arastoopour Irgens
• 金额: $ 31.43万
• 依托单位: Clemson University
• 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: 2020-08-15 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2024965&HistoricalAwards=false
• 关键词: Modeling; measuring; critical; data; literacies

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.

社会对数字技术的依赖导致了正在记录，分类和分析的大量数据。在提高人类效率和生活质量的同时，数据分析还可以再现不平等的不平等，并进一步将包括妇女，有色人种以及生活在贫困中的人群中的人口中的人口边缘化。这项为期两年的STEM教育研究人员研究人员开发项目通过为中学生开发数据科学教育计划来解决这个问题，该计划研究了数字技术的社会和道德维度。通过与100多名导师，父母，学生和研究人员合作作为数据科学教育计划的共同设计者，该计划有可能教育一系列利益相关者在计算教育方面。此外，它有可能通过为STEM的年轻人提供丰富且具有文化相关的经验，从而扩大参与STEM的参与，这可能会激发他们追求STEM专业和职业。特定的项目研究目标是：（1）衡量和与社会，道德，与数字技术相关的社会，与数字技术相关的环境中的衡量和模拟青年的数据科学知识和模型； （2）根据数字技术的道德使用来衡量青年的赋权感，以实施社区的变化。该项目将数据科学教育研究和社会文化学习理论整合在一起，以在社会/道德/政治问题的背景下对数据科学学习的性质建立新的理论理解。这种方法可以促进知识和理解中学年龄的青年如何以其自身文化和更广泛的STEM社区中的价值的方式参与数据实践。该项目还支持开发批判数据科学学习理论的长期目标，以及如何使青年参与社区计划，以促进道德，文化反应灵敏和批判性的STEM学习机会。专业发展目标是建立主要研究者对参与设计的理解，在非正式学习环境中为青年设计的能力以及获得定量民族志学工具和方法的访问权限。通过EHR核心研究支持该项目：STEM教育研究的建立能力（ECR：BCSER）（ECR：BCSER）旨在在旨在进行高质量的STEM学习和茎的研究。奖项反映了NSF的法定任务，并通过使用基金会的知识分子优点和更广泛的影响审查标准评估被认为是宝贵的支持。

项目成果

Designing with and for Youth: A Participatory Design Research Approach for Critical Machine Learning Education

与青年一起设计并为青年设计：批判性机器学习教育的参与式设计研究方法

• 发表时间: 2022
• 期刊: Educational technology society
• 作者: Arastoopour Irgens, Golnaz;Adisa, Ibrahim Oluwajoba;Bailey, Cinamon;Vega, Hazel
• 通讯作者: Vega, Hazel

Characterizing children’s conceptual knowledge and computational practices in a critical machine learning educational program

在关键的机器学习教育计划中描述儿童的概念知识和计算实践

• DOI: 10.1016/j.ijcci.2022.100541
• 发表时间: 2022
• 期刊: International Journal of Child-Computer Interaction
• 作者: Arastoopour Irgens, Golnaz;Vega, Hazel;Adisa, Ibrahim;Bailey, Cinamon
• 通讯作者: Bailey, Cinamon