论文标题
在线统计学教学
Online Statistics Teaching and Learning
论文作者
论文摘要
对于各个级别的统计课程，在线教学在不同方面构成了挑战。特定的在线挑战包括如何有效和互动地进行探索性数据分析，如何合并统计编程，如何包括个人或团队项目以及如何有效，有效地提出数学推导。 本文借鉴了作者在七个不同的在线统计课程中的经验，以应对上述一些挑战。一门课程是在鲍灵格林州立大学（Bowling Green State University）教授的在线探索数据分析课程。第二个课程是在瓦萨学院（Vassar College）教授的高层贝叶斯统计课程，并通过混合模型在10个文科学院共享。我们ALO描述了杜克大学提供的五道菜MOOC专业。
For statistics courses at all levels, teaching and learning online poses challenges in different aspects. Particular online challenges include how to effectively and interactively conduct exploratory data analyses, how to incorporate statistical programming, how to include individual or team projects, and how to present mathematical derivations efficiently and effectively. This article draws from the authors' experience with seven different online statistics courses to address some of the aforementioned challenges. One course is an online exploratory data analysis course taught at Bowling Green State University. A second course is an upper level Bayesian statistics course taught at Vassar College and shared among 10 liberal arts colleges through a hybrid model. We alo describes a five-course MOOC specialization on Coursera, offered by Duke University.
