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Collaborative Research: Streams of Data: Nurturing Data Literacy in Young Science Learners

合作研究：数据流：培养年轻科学学习者的数据素养

基本信息

批准号：
1906286
负责人：
Edward Robeck
金额：
$ 49.19万
依托单位：
American Geological Institute
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-07-01 至 2024-06-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1906286&HistoricalAwards=false
关键词：
Collaborative Research Streams Data Nurturing

项目摘要

Streams of Data: Informing Science, Technology, Engineering, and Mathematics Curriculum Design Through a Study of How Elementary Students Make Meaning of Professionally Collected Real-World Data Data literacy is essential for working with scientific data sets, but educators know very little about how to prepare students for the issues involved in making appropriate inferences from data. This need is compounded by the fact that studies that exist have worked with data sets that students themselves collected, whereas the many electronic data sets, proliferating in the public domain, pose different challenges. This project will develop and study an approach to support fourth grade students' data literacy with complex, large-scale, professionally collected data sets. The work will focus on analytical thinking as a subset of data literacy, specifically evaluating and interpreting data. The project will teach students about working with geoscience data, which connect to observable, familiar aspects of the natural world and align with Earth science curriculum standards. An interdisciplinary team of educators, researchers, and scientists from the Oceans of Data Institute at Educational Development Center and the American Geological Institute will (1) conduct baseline research to understand students' natural affinities for understanding inference from complex data and phenomena; (2) develop and test scaffolding activities that leverage students' intellectual assets and minimize barriers to analytical thinking with professionally collected data; and (3) examine the degree to which the resulting activities support students to do productive work with professionally collected data. In developing an instructional approach, the project informs generally how professionally collected, scientific data can be used to support elementary students to develop data literacy skills. Hypothesizing that science, technology, engineering, and mathematics (STEM) education generally can benefit from the instructional use of complex, large, interactive, and professionally-collected (CLIP) data sets (e.g., related to precipitation, stream flow, and groundwater levels), this study will explore approaches to integrating those data into fourth grade classroom instruction. The research is based on a premise that students who engage with CLIP data early in their classroom STEM experiences will develop skills and attitudes that promote meaningful analyses of those data earlier than if that exposure is delayed until secondary courses. The project will use a three-phase iterative design that will unfold in three urban and suburban school districts in Virginia and Maryland. Phase one will focus on creating a baseline of the reasoning students employ when making inferences from data. It will involve 45 students from grades 3-5 in targeted interviews, which will be recorded, transcribed and analyzed. Phases two and three will focus on design and development in grade 4. Phase two will develop and test activities through an iterative design plan that employs a semi-clinical method with small groups of students. Phase three will implement the activities that result from that process in six classrooms across three districts with approximately 150 students. A scoring rubric that captures student learning will be constructed in phase two and used to measure impacts of the field testing in phase three. Observations and interviews will also be conducted at field sites to understand what students learn about analytical thinking from the activities. The Discovery Research K-12 program (DRK-12) seeks to significantly enhance the learning and teaching of science, technology, engineering and mathematics (STEM) 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.

数据流：通过研究小学生如何理解收集的真实世界数据的意义来告知科学，技术，工程和数学课程设计数据素养对于使用科学数据集至关重要，但教育工作者对如何让学生为从数据中做出适当推断所涉及的问题做好准备知之甚少。现有的研究都是使用学生自己收集的数据集，而在公共领域激增的许多电子数据集构成了不同的挑战，这一事实加剧了这一需要。本计画将发展及研究一种方法，以支援四年级学生的资料素养，并提供复杂、大规模、专业的资料搜集。这项工作将侧重于分析思维作为数据素养的一个子集，特别是评估和解释数据。该项目将教学生如何使用地球科学数据，这些数据与自然世界的可观察，熟悉的方面相联系，并与地球科学课程标准保持一致。一个由教育发展中心数据海洋研究所和美国地质研究所的教育工作者、研究人员和科学家组成的跨学科团队将（1）进行基线研究，以了解学生对理解复杂数据和现象推理的自然亲和力;（二）开发和测试脚手架活动，利用学生的智力资产，并尽量减少分析思维的障碍，收集的数据;以及（3）检查由此产生的活动在多大程度上支持学生使用专业收集的数据进行生产性工作。在开发教学方法时，该项目一般告知如何专业收集，科学数据可以用来支持小学生发展数据素养技能。假设科学，技术，工程和数学（STEM）教育通常可以从复杂，大型，交互式和专业收集（CLIP）数据集（例如，本研究将探讨如何将这些数据整合到四年级的课堂教学中。该研究基于一个前提，即在课堂STEM体验早期接触CLIP数据的学生将培养技能和态度，促进对这些数据进行有意义的分析，而不是将这种接触推迟到中学课程。该项目将采用三阶段迭代设计，将在弗吉尼亚州和马里兰州的三个城市和郊区学区展开。第一阶段将专注于创建学生在从数据中进行推理时使用的推理基线。它将涉及45名3-5年级的学生进行有针对性的访谈，这些访谈将被记录、转录和分析。第二和第三阶段将侧重于4年级的设计和开发。第二阶段将通过迭代设计计划开发和测试活动，该计划采用半临床方法，由小群学生组成。第三阶段将在三个地区的六个教室开展这一进程产生的活动，约有150名学生。第二阶段将建立一个反映学生学习情况的评分标准，并用于衡量第三阶段实地测试的影响。还将在实地进行观察和访谈，以了解学生从活动中学到了什么分析思维。探索研究K-12计划（DRK-12）旨在通过研究和开发创新资源，模型和工具，显着提高学前班学生和教师的科学，技术，工程和数学（STEM）的学习和教学。DRK-12项目中的项目建立在STEM教育的基础研究以及为拟议项目提供理论和经验依据的先前研究和开发工作的基础上。该奖项反映了NSF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。