A Data Visualization Experience for Preservice STEM Teachers

为职前 STEM 教师提供数据可视化体验

基本信息

  • 批准号:
    2142692
  • 负责人:
  • 金额:
    $ 59.99万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2022
  • 资助国家:
    美国
  • 起止时间:
    2022-10-01 至 2025-09-30
  • 项目状态:
    未结题

项目摘要

The majority of teacher preparation programs do not explicitly teach data literacy skills or how to teach those skills. As a result, in-service teachers often do not feel confident with their own data competencies, and do not integrate data skills and practices into their teaching. Yet the presence of data and data visualizations in society continues to grow. Schools should be training students in how to collect, analyze, visualize, and interpret this data. This project intends to provide higher education faculty with the tools to teach their students (preservice teachers) how to integrate data skills into their future K-8 classrooms. The overarching goal is to create a more data literate society, starting with the youngest learners by setting their teachers up for success to teach them these critical data skills.This project will support higher education faculty in guided efforts to implement data literacy skills into existing STEM education methods courses, thereby providing K-8 preservice teachers the skills and self-efficacy to work with data and integrate data literacy into their future classrooms. Four cohorts of five faculty members each will attend a two-day Faculty Training Institute (FTI) in which they are trained to integrate the five session Curriculum Supplement Initiative (CSI) into their courses. Following the training, faculty will implement the content during an existing education methods course, providing preservice teachers the opportunity to collect, analyze, synthesize, and visualize data. The project has five objectives: (1) scale implementation of the CSI materials to 20 new-to-the-program faculty across the United States over 3 years, (2) examine the development of exploratory data and question-asking skills of preservice K-8 STEM teachers (at least 400 in total), (3) examine preservice teachers’ self-efficacy in teaching with STEM data, (4) refine and publish CSI materials aimed at increasing preservice K-8 STEM teachers' exploratory data skills and self-efficacy with the larger community, and (5) broaden the reach of the approach by supporting faculty to share the project with wider audiences through broader impact initiatives. To achieve each of the above objectives, the project team plans to: (1) recruit a geographically and demographically diverse set of faculty teaching education methods courses through STEM education professional organizations, (2) assess preservice teachers’ data literacy skills at the beginning and end of the semester in which the CSI is implemented, (3) assess preservice teachers’ data self efficacy at the beginning and end of the semester in which the CSI is implemented, (4) complete two evidence-based revision iterations of the CSI materials, then make the CSI available for public use, and (5) provide support for faculty who have implemented the CSI to attend conferences and design professional development sessions to share with the broader community. This project intends to refine and disseminate a model for training preservice K-8 teachers to work with and use STEM data in their future classes, and contribute to theory by investigating how preservice teachers’ skills about asking questions related to data changes over time. The project has the potential to fundamentally change the way teacher education programs train preservice teachers to work with data, which can in turn improve the quality of data education for the nation’s youngest learners, resulting in a more data literate society. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools. Partial funding for this project is from the Robert Noyce Teacher Scholarship program.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.
大多数教师培训计划没有明确教授数据素养技能或如何教授这些技能。因此,在职教师往往对自己的数据能力没有信心,也没有将数据技能和实践融入到教学中。然而,数据和数据可视化在社会中的存在继续增长。学校应该培训学生如何收集、分析、可视化和解释这些数据。该项目旨在为高等教育教师提供工具,教他们的学生(兼职教师)如何将数据技能整合到未来的K-8教室中。总体目标是创造一个更有数据素养的社会,从最年轻的学习者开始,让他们的老师成功地教他们这些关键的数据技能。该项目将支持高等教育教师在指导下努力将数据素养技能纳入现有的STEM教育方法课程,从而为K-8幼儿园教师提供使用数据的技能和自我效能,并将数据素养融入他们未来的课堂。四组五名教师将参加为期两天的教师培训学院(FTI),在那里他们接受培训,将五个会议课程补充倡议(CSI)纳入他们的课程。培训结束后,教师将在现有的教育方法课程中实施这些内容,为在职教师提供收集,分析,综合和可视化数据的机会。该项目有五个目标:(1)在3年内将CSI材料推广到美国20名新入职的教师,(2)检查K-8 STEM教师的探索性数据和提问技能的发展情况(至少400人),(3)用STEM数据考察中学教师的教学自我效能感,(4)完善和发布CSI材料,旨在提高中小学STEM教师的探索性数据技能和与更大社区的自我效能,及(5)支持教职员透过更广泛的影响力计划,与更广泛的受众分享项目,以扩大该方法的影响范围。为实现上述各项目标,项目小组计划:(1)通过STEM教育专业组织招募一批地理位置和人口结构多样化的教师来教授教育方法课程,(2)在实施CSI的学期开始和结束时评估职前教师的数据素养技能,(3)在实施CSI的学期初和学期末评估在职教师的数据自我效能。(4)完成CSI材料的两次循证修订,并将CSI公开使用,及(5)为已实施“学生安全倡议”的教师提供支援,让他们出席会议及设计专业发展课程,与社会各界分享经验。该项目旨在完善和传播一个模型,用于培训兼职K-8教师在未来的课堂上使用STEM数据,并通过调查兼职教师询问与数据相关的问题的技能如何随着时间的推移而变化,为理论做出贡献。该项目有可能从根本上改变教师教育项目培训副教师使用数据的方式,从而提高全国最年轻学习者的数据教育质量,从而形成一个更具数据素养的社会。NSF IUSE:EHR计划支持研究和开发项目,以提高所有学生STEM教育的有效性。通过学生的学习轨道,该计划支持创建,探索和实施有前途的做法和工具。该项目的部分资金来自Robert Noyce教师奖学金计划。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。

项目成果

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Melissa Zrada其他文献

What kinds of questions do students ask while exploring data visualizations?
学生在探索数据可视化时会问哪些类型的问题?
  • DOI:
    10.1080/10899995.2019.1675447
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    K. Kastens;Melissa Zrada;M. Turrin
  • 通讯作者:
    M. Turrin
How Do Gestures Reflect Thought and When Do They Affect Thought
手势如何反映思想以及何时影响思想
  • DOI:
  • 发表时间:
    2018
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Melissa Zrada
  • 通讯作者:
    Melissa Zrada

Melissa Zrada的其他文献

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