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.

该项目将通过让高中生了解量化自我来提高他们的数据素养——将设计使用技术来跟踪和反思自己的生物、行为、身体和/或情感数据的实践。为了激发对科学的广泛兴趣，并帮助学生形成关于人类生成的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课程和专业发展材料。学生和老师可以探索、分析和创作小说，由可穿戴生物传感设备记录的多模态和交互式数据表示，学生将了解如何通过动手 STEM 活动（包括创建交互式数据表示）来捕获和解释来自自己身体的数据。学生将参与讨论，考虑使用数据驱动的服务、应用程序和技术的隐私影响，并批判性地评估他们的个人数据的使用方式。项目结束后，讲师学生将有机会与使用生物传感和可穿戴技术的行业合作伙伴建立联系，并获得与这些和相关数据技术领域相关的职业和大学准备资源。该项目将研究基于相关数据的交互式和多模式数据参与工具量化的自我体验可以支持学生学习和参与数据、（神经）生物学和生物信息学。为了实现这一目标，该项目将与教师合作，采用文化响应式、参与式设计来设计工具和材料。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融入情境。数据科学、生物学和生物信息学领域的职业意识将通过调查、访谈和学生作品收集，分析方法将包括定性和定量方法，以了解数据科学、生物学和生物信息学的影响。关于学生学习和参与的项目。该项目通过让学生创建新颖的多模式数据表示并评估自己的数据，解决了培养数据和科学素养、增加对 STEM/ICT 领域的参与以及促进 STEM/ICT 劳动力和职业准备的公平性等普遍挑战。旨在使他们能够使用数据和科学作为工具来生成有关他们关心的问题的知识，并考虑数据相关领域的职业。该项目预计在项目期限内覆盖 25 名教师、15 名导师和 400-600 名学生。该项目由学生和教师创新技术体验 (ITEST) 计划资助，该计划支持加深对实践、计划要素、背景和流程的理解，从而有助于增加学生的知识和能力。对科学、技术、工程和数学 (STEM) 以及信息和通信技术 (ICT) 职业的兴趣。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。