The Accuracy of Causal Learning Over Long Timeframes: An Ecological Momentary Experiment Approach
The Accuracy of Causal Learning Over Long Timeframes: An Ecological Momentary Experiment Approach
复制标题
DOI：
10.1111/cogs.12985
复制
发表时间：
2021-07-01
影响因子：
2.5
通讯作者：
Rottman, Benjamin M.
中科院分区：
文献类型：
--
作者：
Willett, Ciara L.;Rottman, Benjamin M.
从经验中学习因果关系的能力对于人类的适应性行为--选择带来预期效果的原因--至关重要。然而，传统的基于经验的学习实验涉及人为压缩时间的事件，以便所有学习都在几分钟内发生。因此，这些范式完全依赖于工作记忆。相比之下，在现实世界中，我们需要能够在几天或几周内学习因果关系，这需要长期记忆。413名参与者完成了一项智能手机研究，该研究将每天一次试验持续24天与传统的24次连续试验的因果关系进行了比较。令人惊讶的是，我们发现短期与长期之间几乎没有差异。受试者能够准确地检测生成和预防的因果关系，他们表现出虚幻的相关性，在短期和长期的任务。这些结果提供了初步的证据，经验为基础的学习在长时间内表现出类似的优势和弱点，在短时间内。然而，长时间的学习可能会因为更复杂的任务而受到更大的损害。
The ability to learn cause-effect relations from experience is critical for humans to behave adaptively - to choose causes that bring about desired effects. However, traditional experiments on experience-based learning involve events that are artificially compressed in time so that all learning occurs over the course of minutes. These paradigms therefore exclusively rely upon working memory. In contrast, in real-world situations we need to be able to learn cause-effect relations over days and weeks, which necessitates long-term memory. 413 participants completed a smartphone study, which compared learning a cause-effect relation one trial per day for 24 days versus the traditional paradigm of 24 trials back- to- back. Surprisingly, we found few differences between the short versus long timeframes. Subjects were able to accurately detect generative and preventive causal relations, and they exhibited illusory correlations in both the short and long timeframe tasks. These results provide initial evidence that experience-based learning over long timeframes exhibits similar strengths and weaknesses as in short timeframes. However, learning over long timeframes may become more impaired with more complex tasks.