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Collaborative Research: Fostering Virtual Learning of Data Science Foundations with Mathematical Logic for Rural High School Students

协作研究：促进农村高中生数据科学基础与数学逻辑的虚拟学习

基本信息

批准号：
2201394
负责人：
Wanli Xing
金额：
$ 100万
依托单位：
University of Florida
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-07-15 至 2026-06-30
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2201394&HistoricalAwards=false
关键词：
Collaborative Research Fostering Virtual Learning

项目摘要

Data science is revolutionizing science and industry, and the current job market has shown a strong demand for a workforce fluent in data science. The LogicDataScience (LogicDS) curriculum in the Florida Virtual Schools (FLVS) is introducing high school students to this exciting area and related careers. The project addresses a major educational barrier, namely that rural students are less likely to choose a major in STEM and have far less access to advanced STEM courses taught by highly qualified teachers. The LogicDS curriculum and virtual delivery are expected to relieve the resource constraints significantly and thus reach rural students. The strategy behind this curriculum development for data science explores the utility of emphasizing how the foundations of data science in computing, mathematics, and statistics are unified by mathematical logic. The project is studying the impacts of the new curriculum on students’ learning of computing, mathematics, and statistics. At the core of the proposed curriculum is a principled, unified, and novel approach naturally and rigorously integrating the foundations of data science in computing, mathematics, and statistics through mathematical logic. The foundations of computing, mathematics, and statistics are contextualized in each other and in real-life, data-rich problems in this curriculum. This approach does two things that hold fundamental promise for data science education. First, it draws relations between statistics and computing in ways that are helpful for data science learners. Second, it reduces cognitive load and makes learning of key constructs of data science more accessible. A design-based research paradigm guides the project, which is directly impacting about 1,000 students. The project uses microgenetic analysis to study the mechanisms underlying student learning premised by the rationale of the curriculum. In addition, a quasi-experimental study is being employed to investigate comparatively the impact of the new curriculum on students’ learning of computing, mathematics, and statistics and in what way it affects their learning. The Discovery Research preK-12 program (DRK-12) seeks to significantly enhance the learning and teaching of STEM subjects by preK-12 students and teachers, through research and development of innovative resources, models and tools. Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for proposed projects.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.

数据科学正在彻底改变科学和工业，目前的就业市场已经显示出对精通数据科学的劳动力的强烈需求。佛罗里达虚拟学校（FLVS）的LogicDataScience （LogicDS）课程正在向高中生介绍这一令人兴奋的领域和相关职业。该项目解决了一个主要的教育障碍，即农村学生不太可能选择STEM专业，也很少有机会获得由高素质教师教授的高级STEM课程。LogicDS课程和虚拟教学有望显著缓解资源限制，从而惠及农村学生。数据科学课程开发背后的策略探讨了强调如何通过数学逻辑统一计算、数学和统计学中的数据科学基础的实用性。该项目正在研究新课程对学生学习计算机、数学和统计学的影响。所建议课程的核心是一个有原则的、统一的、新颖的方法，通过数学逻辑自然而严格地整合数据科学在计算、数学和统计学中的基础。在本课程中，计算、数学和统计学的基础相互关联，并结合现实生活中数据丰富的问题。这种方法做了两件事，为数据科学教育带来了根本性的希望。首先，它以对数据科学学习者有帮助的方式描绘了统计学和计算之间的关系。其次，它减少了认知负荷，使学习数据科学的关键结构更容易。以设计为基础的研究范式指导了这个项目，它直接影响了大约1000名学生。该项目使用微遗传学分析来研究基于课程基本原理的学生学习机制。此外，还采用准实验研究的方法，比较调查了新课程对学生计算机、数学和统计学学习的影响，以及在何种程度上影响学生的学习。探索研究项目（DRK-12）旨在通过研究和开发创新资源、模型和工具，显著提高幼儿园至12年级学生和教师对STEM学科的学习和教学。DRK-12计划中的项目建立在STEM教育的基础研究和先前的研究和开发工作的基础上，为拟议的项目提供了理论和实证依据。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。