How to improve statistical thinking: Choose the task representation wisely and learn by doing
How to improve statistical thinking: Choose the task representation wisely and learn by doing
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如何提高统计思维：明智地选择任务表示并边做边学
DOI：
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发表时间：
2000
期刊：
影响因子：
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通讯作者：
P. Sedlmeier
中科院分区：
文献类型：
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作者：
P. Sedlmeier
尝试教统计思维使用纠正反馈或“规则培训”的方法已经只有适度的成功。提出了一种新的训练方法，它依赖于假设，即人类的头脑自然地配备了解决任何统计任务，其中相关信息是以绝对频率而不是概率来表示的。在对这种方法的一项调查中，人们被训练使用频率网格来表示概率信息来解决涉及合取概率和条件概率的任务。在以往的培训研究中，“做中学"的重要性被忽视，但在当前的培训中，”做中学“已经发挥了重要作用。研究1表明，结合外部图像表征和边做边学的训练对人们解决合取概率任务的能力有着巨大而持久的影响。天花板效应阻止了频率网格和传统的图形表示法（维恩图）在有效性方面的比较。然而，在研究2中发现网格表示更有效，它处理了更困难的条件概率主题。这些结果为优化统计思维教学和统计信息在媒体中的呈现提供了方法。
Attempts to teach statistical thinking usingcorrective feedback or a “rule-training” approach havebeen only moderately successful. A new trainingapproach is proposed which relies on the assumptionthat the human mind is naturally equipped to solvemany statistical tasks in which the relevantinformation is presented in terms of absolutefrequencies instead of probabilities. In aninvestigation of this approach, people were trained tosolve tasks involving conjunctive and conditionalprobabilities using a frequency grid to representprobability information. It is suggested that learningby doing, whose importance was largely neglected inprior training studies, has played a major role in thecurrent training. Study 1 showed that training thatcombines external pictorial representations andlearning by doing has a large and lasting effect onhow well people can solve conjunctive probabilitytasks. A ceiling effect prevented comparison of thefrequency grid and a conventional pictorialrepresentation (Venn diagrams) with respect toeffectiveness. However, the grid representation wasfound to be more effective in Study 2, which dealtwith the more difficult topic of conditionalprobabilities. These results suggest methods tooptimize the teaching of statistical thinking and thepresentation of statistical information in themedia.
影响因子：
5.4
作者：
Kahneman, D;Tversky, A
通讯作者：
Tversky, A