Modules for Statistics Graduate Teaching Assistants Learning to Teach Equitably with Authentic Data

统计学研究生助教学习如何使用真实数据进行公平教学的模块

• 批准号: 2315435
• 负责人: Jennifer Green
• 金额: $ 12.44万
• 依托单位: Michigan State University
• 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
• 起止时间: 2023-07-15 至 2026-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2315435&HistoricalAwards=false
• 关键词: Modules; Statistics; Graduate; Teaching; Assistants

This project aims to serve the national interest by designing and assessing resources for statistics graduate teaching assistants (GTAs). An overall goal is for GTAs to teach equitably with authentic data. Reforming introductory statistics is becoming increasingly important since statistical thinking plays a key role in harnessing the data revolution in a wide range of workplaces and in a variety of disciplines. Despite a call for introductory statistics instruction that: (1) integrates real data with a context and a purpose, (2) teaches statistics as an investigative process, and (3) fosters active learning, many statistics teaching practices are inconsistent with these recommendations. Instead, statistics courses often focus on procedural skills, which may not lead to meaningful understanding of the power of statistical modeling and concepts in authentic contexts. This project will address the urgent need to improve introductory statistics instruction by designing and implementing a set of modules for discipline-specific professional development for statistics GTAs. The significant outcomes of this project could include the development of GTAs who teach equitably with authentic data, as well as advancement of the current understanding of teacher learning of GTAs in professional community settings.Guided by a design and development research approach, the project will: (1) design a set of four research-informed modules for statistics GTAs learning to teach equitably with authentic data (LEAD Modules), (2) implement LEAD Modules with two GTA communities teaching introductory statistics courses at North Carolina State University and Michigan State University, and (3) further refine LEAD Modules based on design-based research that examines GTA development and their communities. LEAD Modules focus on: (a) teaching statistical thinking, (b) facilitating the model "launch, explore, and discuss," (c) enacting teacher discourse moves, and (d) promoting participatory equity. By drawing on the interdisciplinary expertise of the principal investigators, the project infuses knowledge bases and resources from statistics education and teacher education to support statistics GTAs' learning to teach equitably with authentic data. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through its 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.

该项目旨在通过设计和评估统计学研究生助教（gta）的资源，为国家利益服务。gta的总体目标是公平地使用真实数据进行教学。改革入门统计正变得越来越重要，因为统计思维在广泛的工作场所和各种学科中发挥着利用数据革命的关键作用。尽管有人呼吁统计学入门教学：(1)将真实数据与背景和目的结合起来，(2)将统计学作为一种调查过程来教授，(3)促进主动学习，但许多统计学教学实践与这些建议不一致。相反，统计课程往往侧重于程序技能，这可能不会导致对真实环境中统计建模和概念的力量的有意义的理解。该项目将通过设计和实施一套针对特定学科的gta统计专业发展的模块，解决改进统计入门教学的迫切需要。这个项目的重要成果可能包括发展使用真实数据公平教学的gta，以及推进目前对专业社区环境中教师学习gta的理解。在设计和开发研究方法的指导下，该项目将：(1)为GTA设计一套4个基于研究的统计模块（LEAD模块），以帮助GTA学会用真实数据公平地进行教学（LEAD模块）；(2)与在北卡罗来纳州立大学和密歇根州立大学教授统计学入门课程的两个GTA社区一起实施LEAD模块；(3)基于基于设计的研究进一步完善LEAD模块，研究GTA的发展及其社区。LEAD模块侧重于：(a)教授统计思维，(b)促进模型的“启动、探索和讨论”，(c)制定教师话语动作，以及(d)促进参与性公平。通过利用主要研究人员的跨学科专业知识，该项目注入了统计教育和教师教育的知识库和资源，以支持统计gta学会用真实的数据公平地教学。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。通过其参与学生学习轨道，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。