An inquiry-based, supportive approach to statistical reasoning and application

基于探究的、支持性的统计推理和应用方法

• 批准号: 0942246
• 负责人: Lisa Dierker
• 金额: $ 17.5万
• 依托单位: Wesleyan University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-01-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0942246&HistoricalAwards=false
• 关键词: inquiry; based; supportive; approach; statistical

A uniquely collaborative, inquiry-based course in introductory statistics is developed to serve 100 students per semester across both divisional and departmental boundaries. The curriculum combines new learning materials and innovative teaching strategies to pursue a multidisciplinary model of statistical inquiry, providing training in flexible application of knowledge, opportunities to analyze data in real world contexts, and education about statistical concepts through computing. A comprehensive resource infrastructure is established to provide intense multilevel support to students, allowing them to work independently and creatively to explore their own scientific questions and make decisions about data analysis. The resources that students utilize will be dictated by their research question and results at each stage of their work. That is, beyond basic data management and hypothesis testing themes, students are learning most about what they need to know to answer their specific research questions by doing the work themselves. The course represents 50% of the student's semester curriculum, permitting full immersion in the process. Substantial recruitment efforts are focused on engaging women and underrepresented students during their freshman year, so that their experience can maximally impact the direction of their undergraduateeducation. The broader impact is to provide more quantitatively literate individuals, and a larger, more gender and ethnically-balanced population with the kind of skills needed to communicate quantitative information across disciplines. Finally, a strategy is developed to disseminate the course model and to make the newly developed teaching tools and supportive resources widely available to other universities.

开发了一门独特的协作式、基于探究的统计入门课程，每学期为跨部门和院系边界的 100 名学生提供服务。该课程结合了新的学习材料和创新的教学策略，追求统计探究的多学科模式，提供知识灵活应用的培训、在现实世界中分析数据的机会以及通过计算进行统计概念的教育。建立了全面的资源基础设施，为学生提供强有力的多层次支持，使他们能够独立、创造性地探索自己的科学问题并做出数据分析决策。学生利用的资源将取决于他们的研究问题和每个工作阶段的结果。也就是说，除了基本的数据管理和假设检验主题之外，学生们还可以通过自己的工作来了解回答特定研究问题所需的知识。该课程占学生学期课程的 50%，让学生能够完全沉浸在这个过程中。大量招聘工作的重点是在大一期间吸引女性和代表性不足的学生，以便她们的经验能够最大程度地影响本科教育的方向。更广泛的影响是为更多具有定量知识的个人以及更多、性别和种族更加平衡的人口提供跨学科交流定量信息所需的技能。最后，制定了一项战略来传播课程模式，并将新开发的教学工具和支持资源广泛提供给其他大学。