A Data Visualization Experience for Preservice STEM Teachers

大多数教师培训计划并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缺乏信心，也没有将数据技能和实践融入到他们的教学中。然而，数据和数据可视化在社会中的存在仍在继续增长。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(职前教师)如何将数据技能整合到他们未来的K-8课堂中。该项目的总体目标是创建一个更懂数据的社会，从最年轻的学习者开始，让他们的老师成功地教授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落实到现有的STEM教育方法课程中，从而为K-8职前教师提供处理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，每组五名教员将参加为期两天的教师培训学院(FTI)，在那里他们接受培训，将五节课程补充计划(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，为职前教师提供收集、分析、综合和可视化数据的机会。该项目有五个目标：(1)在3年内向全美20名新入职教师大规模实施CSI材料，(2)检查K-8职前STEM教师(总共至少400人)的探索数据和提问技能的发展，(3)检查职前教师在使用STEM数据进行教学时的自我效能，(4)完善和出版CSI材料，旨在提高K-8职前STEM教师的探索数据技能和对更大社区的自我效能感，以及(5)通过支持教员通过更广泛的影响计划与更广泛的受众分享项目来扩大方法的覆盖范围。为了达到上述目标，项目组计划：(1)通过STEM教育专业组织招聘一套地理和人口结构不同的教员教学方法课程；(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的学期开始和结束时评估职前教师的数据自我效能；(4)完成CSI材料的两次循证修订迭代，然后将CSI提供给公众使用，以及(5)为已实施CSI的教师提供支持，让他们参加会议和设计专业发展会议，与更广泛的社区分享。该项目旨在改进和传播一个培训K-8职前教师在未来课堂上使用和使用STEM数据的模式，并通过调查职前教师如何随着时间的推移提出与数据变化相关的问题的技能来为理论做出贡献。该项目有可能从根本上改变教师教育项目培训职前教师使用数据的方式，这反过来可以提高美国最年轻学习者的数据教育质量，导致一个更懂数据的社会。NSF IUSE：EHR计划支持研究和开发项目，以提高所有学生的STEM教育的有效性。通过参与式学生学习路径，该计划支持创建、探索和实施有前途的实践和工具。该项目的部分资金来自罗伯特·诺伊斯教师奖学金计划。这一奖项反映了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。

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.