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首页> 外文期刊>Journal of Statistics Education >Modeling First: Applying Learning Science to the Teaching of Introductory Statistics
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Modeling First: Applying Learning Science to the Teaching of Introductory Statistics

机译：第一种建模：将学习科学应用于介绍统计学教学

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摘要

Students learn many concepts in the introductory statistics course, but even our most successful students end up with rigid, ritualized knowledge that does not transfer easily to new situations. In this article we describe our attempt to apply theories and findings from learning science to the design of a statistics course that aims to help students build a coherent and interconnected representation of the domain. The resulting practicing connections approach provides students with repeated opportunities to practice connections between core concepts (especially the concepts of statistical model, distribution, and randomness), key representations (R programming language and computational techniques such as simulation and bootstrapping), and real-world situations statisticians face as they explore variation, model variation, and evaluate and compare statistical models. We provide a guided tour through our curriculum implemented in an interactive online textbook (CourseKata.org) and then provide some evidence that students who complete the course are able to transfer what they have learned to the learning of new statistical techniques.
机译：学生在介绍性统计课程中学会了许多概念，但即使是我们最成功的学生结束了刚性，仪式化的知识也不会轻易转移到新的情况。在本文中，我们描述了我们将学习科学的理论和调查结果应用于旨在帮助学生构建域的连贯和相互连接的表现的统计课程的理论和调查结果。由此产生的练习连接方法为学生提供了重复的机会，以练习核心概念之间的连接（特别是统计模型，分布和随机性的概念），密钥表示（R编程语言和计算技术，例如仿真和自动映射），以及现实世界情况统计学家在探索变化，模型变化和评估和比较统计模型时面临面部。我们通过在互动在线教科书（PrissKata.org）中实现的课程提供了导游，然后提供一些证据表明，完成课程的学生能够转移他们已经学习的新统计技术的学习。

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