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

开发了一门独特的合作、基于探究的统计学入门课程，每学期跨越部门和部门边界为100名学生服务。该课程结合了新的学习材料和创新的教学策略，以追求统计查询的多学科模式，提供灵活应用知识的培训，提供在现实世界背景下分析数据的机会，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，为学生提供密集的多层次支持，使他们能够独立和创造性地探索自己的科学问题，并就数据分析做出决定。学生使用的资源将取决于他们在工作的每个阶段的研究问题和结果。也就是说，除了基本的数据管理和假设检验主题外，学生们通过自己动手完成工作，学到了他们需要知道的大部分知识，以回答他们特定的研究问题。这门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。大量的招聘工作侧重于在大一期间吸引女性和代表性不足的学生，以便她们的经历能够最大限度地影响其本科教育的方向。更广泛的影响是为更多有数量文化的人，以及更多、性别和种族更平衡的人口提供跨学科交流量化信息所需的技能。最后，制定了推广该课程模式的策略，并将新开发的教学工具和支持资源广泛应用于其他大学。

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.