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

一个独特的合作，以探究为基础的课程，在介绍统计开发服务每学期100名学生跨越部门和部门的界限。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，提供灵活应用知识的培训，在现实世界背景下分析数据的机会，以及通过计算学习统计概念的教育。建立了一个全面的资源基础设施，为学生提供强烈的多层次支持，使他们能够独立和创造性地探索自己的科学问题，并对数据分析做出决定。学生使用的资源将根据他们的研究问题和工作的每个阶段的结果而定。也就是说，除了基本的数据管理和假设检验主题之外，学生们通过自己的工作来学习他们需要知道的关于回答他们具体研究问题的大部分知识。该课程占学生学期课程的50%，允许学生完全沉浸在这个过程中。大量的招聘工作集中在招收大一新生的女性和代表性不足的学生，这样他们的经历就能最大限度地影响他们的本科教育方向。更广泛的影响是提供更多具有定量知识的个人，以及一个更大的、性别和种族更平衡的人口，他们拥有跨学科交流定量信息所需的技能。最后，制定了推广课程模式的策略，并使新开发的教学工具和辅助资源在其他大学广泛使用。

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.