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

扩大基于随机化的统计入门课程的影响并评估其有效性

• 批准号: 1323210
• 负责人: Nathan Tintle
• 金额: $ 55.01万
• 依托单位: Dordt University, Incorporated
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-02-15 至 2019-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1323210&HistoricalAwards=false
• 关键词: Broadening; impact; evaluating; effectiveness; randomization; Broadening; impact; evaluating; effectiveness; randomization

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.

该PI团队正在研究两个互补方面，以增加基于随机的新课程的入门统计信息，该课程强调：i）使用基于随机的方法的推理的核心逻辑以及直观，周期性的，活跃的学习教学法，以及II）通过提出问题和收集数据的整体统计调查过程和ii），从而使数据和收集数据进行地下绘画。第一个方面涉及：a）进行一系列十二天的1-4天专业发展研讨会，b）开发和支持在线学习社区，以在研讨会之外提供持续的支持。该项目的智力优点的一个重要方面在于第二个方面，涉及评估模型课程的广泛转移性和研究，以加深对学生课程中学生态度，概念理解和学习轨迹的理解。该团队与研讨会的参与者，开发人员和其他教职员工一起收集了来自各个机构的3000多名学生的大量而多样化的态度和概念评估数据。对学生的发展学习轨迹进行了深入的定性和定量评估，正在进行有关关键概念的发展轨迹。该项目不仅通过其计划的研讨会来实现更广泛的影响，而且还通过通过财团来协调其努力来提高本科统计教育（CAUSA），这是统计教育中变革努力的主要活动中心。