Expanding and assessing the art and practice of statistical thinking

该项目旨在通过为专上统计讲师提供教师专业发展和支持材料来服务于国家利益。该项目旨在拓宽和深化这些教师专注于统计思维的艺术和实践的能力。随着高等教育统计课程的注册人数持续快速增长，有机会扩大统计和数据科学教育中最佳实践的使用。从事数据科学的学生越来越多样化，跨学科数据的作用越来越大，这进一步强调了设计精良、符合21世纪劳动力需求的现代统计学课程的必要性。《统计教育评估和教学指南》（GAISE）强调，需要将统计作为一个调查过程来教授，重点是概念理解、有背景、有目的地使用真实数据、有效利用技术以及为学习提供高质量的评估。然而，许多大专讲师还不熟悉GAISE，许多人没有接受过统计/数据科学方面的正式培训，也没有足够的资源或专业网络。参与学生学习轨道的三级IUSE项目将通过密集的研讨会，持续的互动，形成性评估和支持材料为教师提供专业发展，以显着提高学生的统计教育。该项目将对统计思维艺术和实践方面的教学产生重大影响，与GAISE和当前统计学教与学的研究保持一致。在项目的四年期间，将提供24个面向讲师的讲习班，使用面对面和虚拟方法的混合方法，创建一个由600多名统计教育工作者组成的扩大网络。参与培训的教师将成为持续同步的专业发展项目的一部分，该项目包括社交媒体互动、博客/讨论板机会以及培训后的办公时间支持教师。此外，该项目还将制作免费材料，供教师在课堂上使用。这些免费和广泛传播的材料将包括面向教师的视频、独立于平台的小程序和其他多媒体支持。该项目还将根据参与教师的反馈和国际公认咨询委员会的见解，生成和完善教师和学生的材料。600名参与的教育工作者将在项目期间直接影响超过75000名学生，在项目期间和之后传播材料还会产生额外的影响。教师的工作重点是让学生掌握广泛的技能和背景，从而大大增加学生的多样性，培养他们对统计概念的理解。NSF IUSE: EDU项目支持研究和开发项目，以提高所有学生STEM教育的有效性。通过参与学生学习轨道，该计划支持有前途的实践和工具的创建，探索和实施。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。

This project aims to serve the national interest by providing faculty professional development and support materials to post-secondary statistics instructors. The project looks to broaden and deepen the ability of these instructors to focus on the art and practice of statistical thinking. As post-secondary statistics course enrollments continue growing rapidly, there is an opportunity to expand the use of best practices in statistics and data science education. The increasingly diverse population of students engaging in data science and the increased role of data across disciplines further underscores the need for well-designed, modern statistics courses aligned with the 21st century workforce. The Guidelines for Assessment and Instruction in Statistics Education (GAISE) have emphasized the need to teach statistics as an investigative process, with a focus on conceptual understanding, use of real data with context and purpose, effective use of technology, and high-quality assessments for learning. However, many post-secondary instructors are not yet familiar with GAISE, and many do not have formal training in statistics/data science or sufficient access to resources or professional networks. This Level III IUSE project in the Engaged Student Learning track will provide faculty professional development through intensive workshops, sustained interactions, formative assessment, and support materials to dramatically improve students’ statistical education. This project will have substantial impact on instruction in the art and practice of statistical thinking, aligned with GAISE and current research on teaching and learning in statistics.Over the four-year period of the project, 24 instructor-facing workshops will be offered using a mix of in-person and virtual approaches, creating an expanded network of over 600 statistics educators. Participating instructors will be part of a sustained synchronous professional development program that includes social media interaction, blog/discussion board opportunities, and office hours to support instructors post-workshop. Furthermore, the project will produce freely-available materials for instructors to use in their classrooms. These free and widely disseminated materials will include instructor-facing videos, platform-independent applets, and other multi-media supports. The project will also generate and refine faculty and student materials based on feedback from participating instructors and insights from an internationally recognized advisory board. The 600 participating educators will directly impact over 75,000 students during the project period, with additional impact arising from dissemination of materials during and beyond the life of the project. Efforts are particularly focused on instructors reaching students with a broad selection of skills and backgrounds, leading to a substantial increase in the diversity of students developing their conceptual understanding of statistics. The NSF IUSE: EDU 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.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.