Minimizing learning behavior in repeated real-effort tasks
Minimizing learning behavior in repeated real-effort tasks
复制标题
最大限度地减少重复的真实任务中的学习行为
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
C. Sölch
中科院分区：
文献类型：
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作者：
V. Benndorf;Holger Andreas Rau;C. Sölch
本文讨论了学习行为和被试在实际任务中执行能力的异质性。之后，我们提出了一个新的变种Erkal等人。S（2011）加密实排序任务，旨在最小化重复设置中的学习行为。在任务中，参与者将单词加密成数字。在我们的变体中，我们应用双随机化机制来最小化学习和异质性。现有的重复实时排序任务的实验发现，上半年和下半年之间的性能提高了12-14%。相比之下，我们的任务在上半年和下半年之间将学习行为降低到2%。数据显示，受试者表现出较小的异质性。JEL分类编号：C90、C91。
In this paper, we discuss learning behavior and the heterogeneity of subjects’ ability to perform in real-e↵ort tasks. Afterwards, we present a novel variant of Erkal et al.’s (2011) encryption real-e↵ort task which aims to minimize learning behavior in repeated settings. In the task, participants encrypt words into numbers. In our variant, we apply a double-randomization mechanism to minimize learning and heterogeneity. Existing experiments with repeated real-e↵ort tasks find a performance increase of 12-14% between the first and second half. By contrast, our task mitigates learning behavior down to 2% between the first and second half. The data show that subjects show a small heterogeneity in performance. JEL Classification numbers: C90, C91.