一个大规模的选择和响应时间数据数据集在时间间选择中
Hannah Pongratz1, Martin Schoemann2
1Department of Psychology, University of Mannheim, 68131, Mannheim, Germany. hannah.pongratz@uni-mannheim.de.
Scientific data
|March 3, 2026
概括
这项研究引入了大量的时间间选择 (ITC) 和响应时间数据集,解决了行为经济学研究中的差距. 这些数据旨在推进认知过程模型,以了解决策.
科学领域:
- 行为经济学是一种行为经济学.
- 认知心理学 认知心理学
- 决策科学 决策科学 决策科学
背景情况:
- 时间间选择 (ITC) 研究传统上侧重于决策,忽视了潜在的认知过程.
- 信息通信的流程模型需要流程数据,例如响应时间 (RTs),这些数据未得到充分利用.
- 越来越需要全面的数据来开发更复杂的ITC理论.
研究的目的:
- 呈现一个大规模的,开放式的数据集的时间间选择 (ITC) 和相关的响应时间 (RTs).
- 促进开发先进的流程模型,以了解ITC.
- 为正在进行的研究贡献创建一个不断扩大的数据库.
主要方法:
- 汇编了100项ITC研究的数据,包括11,852名受试者和1,172,644项试验.
- 收集行为数据 (选择和响应时间).
- 收集方法和样本信息,包括任务程序和激励细节.
主要成果:
- 现在可以获得一个大量的数据集,结合ITC,RT和上下文信息.
- 该数据集为探索决策中的认知过程提供了基础.
- ITC数据库的结构是为了持续增长和社区贡献.
结论:
- 通过包括响应时间数据,提出的数据集解决了ITC研究中的一个关键差距.
- 预计这项资源将为完善关于时间间决策的理论做出重大贡献.
- ITC数据库的开放性和扩展性促进了该领域的协作进步.
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