探索情绪状态与编码任务质量之间的联系:试点研究
Aquib Reshad1, Valentina Nino1, Maria Valero2
1Department of Industrial and Systems Engineering, Kennesaw State University, Marietta, GA, United States.
Frontiers in human neuroscience
|December 11, 2025
概括
这项研究探讨了情绪如何影响编码质量. 大脑活动 (EEG) 和自我报告表明神经情绪标记和程序员表现之间存在联系,尽管需要更多的研究.
科学领域:
- 认知科学 认知科学
- 神经科学是一个神经科学.
- 软件工程 软件工程 软件工程
背景情况:
- 情绪显著影响认知功能,但它们在编程中的作用尚未得到充分理解.
- 了解编程中的情感认知联系可以提高开发人员的生产力和代码质量.
研究的目的:
- 研究情绪状态与编码任务质量的关系.
- 探索使用脑电图 (EEG) 来测量编程期间情绪的可行性.
主要方法:
- 十名参与者执行了一个编程任务,同时使用EEG监测他们的大脑活动.
- 前额α不对称 (FAI) 被用作情绪价值的神经指标.
- 用积极和消极经验量表 (SPANE) 收集了情感自我报告.
- 编码任务的质量是使用标准化标题来评估的.
主要成果:
- 初步分析表明,正面α不对称 (FAI) 与编码性能之间存在潜在的关联.
- 自我报告的情绪状态 (SPANE) 与编码质量的相关性不太一致或较弱.
- 该研究证实了将基于EEG的情绪指标集成到软件工程研究中的可行性.
结论:
- 情绪的神经标记可能与编码性能比自我报告的情绪更密切相关.
- 这项试点研究为未来关于情绪和编程的更大规模研究提供了基础.
- 整合神经科学方法可以为软件开发过程提供新的见解.
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