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研究生教学助理资源（GTA）来服务国家利益。总体目标是GTA用真实的数据公平地教授。改革介绍性统计数据变得越来越重要，因为统计思维在在广泛的工作场所和各种学科中利用数据革命方面起着关键作用。尽管呼吁介绍性统计指令：（1）将真实数据与上下文和目的集成在一起，（2）将统计信息作为调查过程，（3）促进了积极的学习，许多统计学教学实践与这些建议不一致。取而代之的是，统计课程通常专注于程序技能，这可能不会导致对真实背景下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组用于特定于统计的专业发展的模块，以提高迫切需要提高入门统计指令。该项目的重大结果可能包括开发GTA的GTA，这些GTA可以与真实数据公平地教授，以及对专业社区环境中GTA的教师学习的最新理解的发展。在设计和开发研究方法的指导下，该项目将：（1）设计四个研究的研究模块，以与统计数据进行了统计学范围，该模型与认证数据相当（2）（2）（2）（2）（2）（2）（2）（2）（2）模式（2）（2）（2）（2北卡罗来纳州立大学和密歇根州立大学的教学统计课程教学统计课程，以及（3）基于设计基于设计的研究，进一步完善铅模块，该研究研究了GTA发展及其社区。铅模块的重点关注：（a）教学统计思维，（b）促进“启动，探索和讨论”模型，（c）颁布教师话语的动作，以及（d）促进参与式公平。通过利用主要研究人员的跨学科专业知识，该项目从统计学教育和教师教育中注入知识库和资源，以支持统计GTAS的学习，以公平地使用真实的数据进行教学。 NSF IUSE：EDU计划支持研发项目，以提高所有学生STEM教育的有效性。通过其参与的学生学习轨道，该计划支持了有前途的实践和工具的创建，探索和实施。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响评估的评估来支持的。