Broadening the impact and evaluating the effectiveness of randomization-based curricula for introductory statistics

该PI团队正在两个互补的方面开展工作，以增加采用新的基于随机化的入门统计学课程，该课程强调：i)使用基于随机化的方法进行推理的核心逻辑，同时采用直观的、周期性的、主动学习的教学法；ii)统计调查的整个过程，从提问和收集数据到进行推断和得出结论。第一个方面包括：a)举办一系列12个1-4天的专业发展研讨会；b)开发和支持一个在线学习社区，在研讨会之外提供持续的支持。该项目智力价值的一个重要方面在于第二个方面，即评估模式课程的广泛可转移性，并研究如何加深对课程中学生态度、概念理解和学习轨迹的理解。与研讨会参与者、开发人员和其他教师一起，该团队正在从不同机构的3000多名学生那里收集大量不同的态度和概念评估数据。对学生在关键概念上的发展学习轨迹进行深入的定性和定量评估。该项目不仅通过其计划举办的讲习班，而且还通过促进本科统计教育联合会（CAUSE）协调其努力，从而产生更广泛的影响，该联合会是统计教育改革努力的主要活动中心。

This PI team is working on two complementary fronts to increase the adoption of a new randomization-based curricula for introductory statistics that emphasizes: i) the core logic of inference using randomization-based methods alongside an intuitive, cyclical, active-learning pedagogy, and ii) the overall process of statistical investigations, from asking questions and collecting data through making inferences and drawing conclusions. The first front involves: a) conducting a series of twelve 1-4 day professional development workshops, and b) developing and supporting an online learning community to provide on-going support beyond the workshops. An important aspect of the intellectual merit of the project lies in the second front which involves the evaluation of widespread transferability of the model curriculum and research to deepen understanding of students' attitudes, conceptual understanding, and learning trajectories within the curriculum. Together with the workshop participants, developers, and other faculty, the team is gathering a large and diverse set of attitudinal and conceptual assessment data from over 3000 students at a variety of institutions. In-depth qualitative and quantitative assessments of students' developmental learning trajectories on key concepts are being carried out. The project is exercising broader impacts not only through its planned workshops, but also through coordination of its efforts through the Consortium for the Advancement of Undergraduate Statistics Education (CAUSE), which serves as the primary hub of activity for transformational efforts in statistics education.