Collaborative Research: Integrating Students’ Interests, Identities and Ways of Knowing with Network Visualization Tools to Explore Data Literacy Concepts
Collaborative Research: Integrating Students’ Interests, Identities and Ways of Knowing with Network Visualization Tools to Explore Data Literacy Concepts
批准号:
2241706
负责人:
Merijke Coenraad
金额:
$39.8万
依托单位:
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
项目状态:
未结题
起止时间:
2023-05-01 至 2026-04-30
中文摘要
该项目是对越来越多的人认识到青年可以从广泛的数据素养技能中受益这一认识的回应。对于学习者来说,网络可视化是一种特别强大和相关的方法。在网络可视化中,人、地点和事物是网络中的节点,显示为圆形。这些节点由表示交互的线连接。学员可以使用动态可视化查看网络中节点和线之间的关系,也可以查看表格形式的网络数据。这两种不同的表示法结合在一起可以帮助学习者在许多情况下探索数据。这种探索与流行社交媒体平台上建立的关系数据尤其相关。因此,网络可视化提供了一个独特的机会,可以在青年学习者感兴趣和相关的丰富社交环境中探索数据和数据素养。当他们探索跨学科的一系列与当地相关的背景时,学习者将参与核心数据素养原则。为此,项目团队将使用开源网络设计、实施和研究有关网络可视化的教学单元。创建该团队之前创建的软件工具,以支持直观、协作的网络可视化。作为与教师共同设计过程的一部分,该团队将创建一个课程单元,鼓励7年级和8年级的学生参与核心网络可视化和符合纪律标准的关键数据素养实践。课程将整合学生的兴趣和文化认同,以及他们所在社区的兴趣和文化认同。例如,可以探索的网络可视化包括他们所从事的爱好和活动以及他们的文化或身份的各个方面。为了帮助学生更好地欣赏网络可视化,他们将有机会发展、批评和修改他们构建的可视化。这个项目将采取协同的方法,中学生使用网络可视化来了解他们自己和他们的社区。同时,学生还将学习使他们的探索成为可能的基础网络科学和数据素养原则,这些原则是他们使用许多常见技术的核心经验。该项目在这项为期三年的研究中提出了三个研究问题:1)学生如何通过与同龄人创建网络可视化来学习网络和数据素养概念?2)通过学生个人和整体感兴趣的话题来探索他们的集体身份,使用网络可视化如何帮助激励他们探索数据素养,并将技术更深入地融入他们的生活和职业生涯?3)教师在使用网络可视化支持教学数据素养概念方面看到了哪些挑战和机遇?项目小组将与一个伙伴学区进行迭代共同设计,以调整课程草案,使之与当地相关和有意义。该项目还将扩展Net.Create工具,以支持对数据来源等数据素养概念的更强有力的探索。数据分析将包括数据素养概念和关键程度的事前/事后测量,分析学员创建的网络和计算机日志,应用衡量学生参与不同活动的质量的参与度准则,以及课堂活动的互动分析,以帮助阐明学习者如何使用工具发展对目标概念的理解。项目小组将与一年级的两名教师、二年级的三名教师和三年级的五名教师密切合作,同时还将扩大实施规模,看看随后如何能够增加多达20名教师来实施课程。该项目由学生和教师创新技术体验计划(ITEST)资助,该计划支持建立对实践、计划要素、背景和过程的理解的项目,这些项目有助于提高学生对科学、技术、工程和数学(STEM)以及信息和通信技术(ICT)职业的知识和兴趣。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
This project is responding to the growing recognition that youth can benefit from a wide range of data literacy skills. Network visualization is a particularly powerful and relevant approach for learners to understand. In a network visualization, people, places, and things are the nodes in a network, displayed as circles. These nodes are connected by lines that represent interactions. Learners can view relationships between nodes and lines in a network using either a dynamic visualization or they can view network data as a table. The two different representations together can help learners explore data in many contexts. This exploration is particularly relevant for data about relationships built on popular social media platforms. Therefore, network visualizations present a unique opportunity to explore data and data literacy in rich social contexts that are of interest for, and relevance to, youth learners. As they explore a range of locally relevant contexts across disciplines, learners will be engaged with core data literacy principles. To accomplish this, the project team will design, implement, and study an instructional unit about network visualization using the open-source Net.Create software tool that this team previously created to support intuitive, collaborative network visualization. As part of a co-design process with teachers, the team will create a curriculum unit that encourages 7th and 8th grade students to engage in core network visualization and key data literacy practices that meet disciplinary standards. The curriculum will integrate students’ interests and cultural identities, and those of their communities. For example, network visualizations that may be explored include hobbies and activities they are engaged in as well as aspects of their culture or identity. To help students appreciate network visualization in a robust manner, they will have opportunities to develop, critique, and revise the visualizations they build.This project will take a synergistic approach in which middle school students use network visualization to learn about themselves and their communities. As the same time, students will also be learning about the underlying network science and data literacy principles that make their exploration possible, and which are central to their experiences with many common technologies. The project addresses three research questions over this three-year study: 1) How can students learn network and data literacy concepts through the creation of network visualizations with their peers? 2) How does exploring their collective identity, through topics of interest to students both individually and as a whole, using network visualization help motivate them to explore data literacy and integrate technology more deeply into their lives and careers? 3) What challenges and opportunities do teachers see in using network visualizations to support teaching data literacy concepts? The project team will engage in iterative co-design with a partner school district to adapt the draft curriculum to be locally relevant and meaningful. The project will also extend the Net.Create tool to support more robust exploration of the data literacy concepts such as data provenance. Data analysis will include pre / post measures of data literacy concepts and criticality, analysis of networks created by learners and computer logs, application of an engagement rubric that measures quality of student engagement with different activities, and interaction analysis of classroom activities to help articulate how learners used the tools to develop understanding of target concepts. The project team will work closely with two teachers in year 1, three teachers in year 2, and five teachers in year 3, while also scaling up the implementation to see how up to 20 additional teachers are subsequently able to implement the 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.
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Collaborative Research: Modeling inclusive computational thinking instruction: Video cases for developing teacher knowledge
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批准号:2318168
-
项目类别:Continuing Grant
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资助金额:$69.98万
-
财政年份:2023
-
负责人:Merijke Coenraad
-
依托单位:
国内基金
海外基金
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