Promoting Students' Data Literacy through the Creation of Interactive Multimodal Representations of Biometric Data

通过创建生物识别数据的交互式多模态表示来提高学生的数据素养

• 批准号: 2241751
• 负责人: Camillia Matuk
• 金额: $ 129.02万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2027-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2241751&HistoricalAwards=false
• 关键词: Promoting; Students; Data; Literacy; through

This project will promote data literacy in high school students by engaging them in learning about the Quantified Self -- the practice of using technology to track and reflect on one’s own biological, behavioral, physical, and/or emotional data. Learning activities will be designed to spark a broad interest in science and to help develop students’ informed opinions about the role of human-generated data in public life. To achieve this goal, the project will develop and test software tools as well as lesson and professional development materials with which students and teachers can explore, analyze, and create novel, multimodal, and interactive representations of data, recorded by wearable biosensing devices. Students will learn about how data from their bodies can be captured and interpreted through hands-on STEM activities that include the creation of interactive data representations. Students will design and execute small exploration projects to answer their own questions and create offline and online artifacts to communicate their findings. Students will engage in discussions that consider the privacy implications of using data-fueled services, applications, and technologies and critically evaluate how their personal data is being used. During and after the project, instructors and students will have opportunities to connect with industry partners who work with biosensing and wearable technologies, and to access career and college readiness resources relevant to these and related data technology fields.This project will study how interactive and multimodal data engagement tools, grounded in relatable Quantified Self experiences, can support students’ learning and engagement with and about data, (neuro)biology, and bioinformatics. To achieve this, the project will design tools and materials in collaboration with teachers using a culturally responsive, participatory design approach, to ensure that the project activities will appeal to a range of students' interests and that it will promote equity of participation in STEM education. The project will also examine how industry/mentor partnerships and an online platform can help learners contextualize their own cognition and behavior within population-wide patterns and build awareness of careers in data science, biology, and bioinformatics. Data will be collected through surveys, interviews, and student work artifacts. The analysis approach will include both qualitative and quantitative approaches to understand the impact of the project on student learning and engagement. This project addresses the pervasive challenges of building data and science literacy, increasing participation in STEM/ICT fields, and promoting equity in STEM/ICT workforce and career preparation. By engaging students in creating novel, multimodal data representations and evaluating their own data, the project aims to empower them to use data and science as tools for generating knowledge about issues that concern them and to consider careers in data-related fields. The project anticipates reaching 25 teachers, 15 mentors, and 400-600 students within the project term, and more via an open-source software and curriculum. This project is funded by the Innovative Technology Experiences for Students and Teachers (ITEST) program, which supports projects that build understandings of practices, program elements, contexts and processes contributing to increasing students' knowledge and interest in science, technology, engineering, and mathematics (STEM) and information and communication technology (ICT) careers.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.

该项目将通过学习量化的自我来促进高中生的数据素养 - 使用技术跟踪和反思自己的生物学，行为，身体和/或情感数据的做法。学习活动将旨在激发人们对科学的广泛兴趣，并帮助发展学生对人类生成数据在公共生活中的作用的知情意见。为了实现这一目标，该项目将开发和测试软件工具，以及学生和教师可以通过这些材料进行探索，分析和创建数据的新颖，多模式和交互式的数据，并由可穿戴的生物启用设备记录的数据。学生将了解如何通过动手的STEM活动来捕获和解释自己的身体数据，包括创建交互式数据表示。学生将设计和执行小型勘探项目，以回答自己的问题，并创建离线和在线工件以传达他们的发现。学生将进行讨论，这些讨论考虑使用数据燃料服务，应用程序和技术的隐私影响，并认真评估如何使用其个人数据。在项目期间和之后，讲师和学生将有机会与与生物传感和可穿戴技术合作的行业合作伙伴建立联系，并访问与这些和相关数据技术领域相关的职业和大学准备资源。该项目将研究互动和多模式数据参与工具，以相关的量化自我经验为基础，可以支持学生的学习和neurosic和neuro and and and and and and and and and and and and and and and and and and and and and togation和bio and togation and togation and togation and togation和bio and Forgagation and Forgant和bio。为了实现这一目标，该项目将使用具有文化响应的参与设计方法与教师合作设计工具和材料，以确保项目活动将显示出一系列学生的兴趣，并促进参与STEM教育的公平。该项目还将研究行业/导师合作伙伴关系和在线平台如何帮助学习者将自己的认知和行为与人口范围的模式相关联，并在数据科学，生物学和生物信息学方面提高对职业的认识。数据将通过调查，访谈和学生作品工件收集。分析方法将包括定性和定量方法，以了解项目对学生学习和参与的影响。该项目应对建立数据和科学文献的普遍挑战，增加参与STEM/ICT领域，并促进STEM/ICT劳动力和职业准备的公平。通过吸引学生创建新颖的多模式数据表示并评估自己的数据，该项目旨在使他们能够使用数据和科学作为对问题的知识的工具，并考虑与数据相关的领域中的职业。该项目预计在项目学期内将获得25名教师，15名导师和400-600名学生，以及更多通过开源软件和课程。该项目由学生和教师（ITEST）计划的创新技术经验资助，该计划支持对实践，计划要素，环境，环境和流程的理解，从而有助于增加学生对科学，技术，工程和数学和数学（STEM）的知识和兴趣的有助于提高学生的知识和兴趣（STEM），以及对ICT的信息和沟通技术（ICT）的授权，并依靠NSF的宣传奖，并依靠DEEM的宣传来表现出依据，并以此为基础。更广泛的影响审查标准。