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

一个独特的协作，调查为基础的课程，在介绍统计开发服务每学期100名学生跨越两个部门和部门的界限。该课程结合了新的学习材料和创新的教学策略，以追求统计调查的多学科模式，提供灵活应用知识的培训，在真实的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，使他们能够独立工作，创造性地探索自己的科学问题，并对数据分析做出决策。学生利用的资源将由他们的研究问题和结果在他们的工作的每个阶段决定。也就是说，除了基本的数据管理和假设检验主题，学生们通过自己的工作来学习他们需要知道的来回答他们的具体研究问题。该课程占学生学期课程的50%，允许完全沉浸在这个过程中。大量的招聘工作集中在吸引妇女和代表性不足的学生在他们的大一，使他们的经验可以最大限度地影响他们的本科教育的方向。更广泛的影响是提供更多的数量识字的个人，以及更多的性别和种族平衡的人口，他们拥有跨学科交流量化信息所需的技能。最后，制定了一项战略，以传播课程模式，并使新开发的教学工具和支持资源广泛提供给其他大学。

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.