视觉空间自我中心距离的静态估计与代反:一种认知感知任务
Constantin Ciucurel1, Elena Ioana Iconaru1
1Department of Medical Assistance and Physical Therapy, University Center of Pitesti, National University of Science and Technology Politehnica Bucharest, 110040 Pitesti, Romania.
Life (Basel, Switzerland)
|January 28, 2026
概括
代反在大型环境中提高了自我中心的距离估计准确性和效率. 然而,它并没有消除距离压缩,在测试的距离上显示出一致的偏差.
科学领域:
- 认知心理学 认知心理学
- 人类的感知 人类的感知
- 空间认知 空间认知
背景情况:
- 准确的自我中心距离估计对于在大规模环境中的导航和交互至关重要.
- 感知编码和认知重新校准相互作用,影响空间准确性.
- 了解反如何影响空间学习是提高绩效的关键.
研究的目的:
- 研究代,基于反的学习对空间准确性,感知偏差和任务效率的影响.
- 检查参与者在大型户外环境中如何重新校准他们的距离估计.
- 分析特定的绩效指标,包括估计错误,试验次数和试验持续时间.
主要方法:
- 133名参与者使用移动网络应用程序进行了户外距离估计,并立即进行了校正反.
- 对134米,575米和1463米的目标进行了估计.
- 由于数据分布不正常,使用了非参数统计测试 (弗里德曼,威尔科克森签名等级).
主要成果:
- 对于所有分析变量 (p < 0.001) 在所有距离上都发现了显著的主体内效应.
- 估计误差从134米的高估转移到575米和1463米的低估 (p < 0.0167).
- 对于最远的目标,尝试数量增加,表明认知负载较高,而试验持续时间显示非线性适应.
结论:
- 代反增强了感知稳定性和任务效率,但并没有消除固有的距离压缩偏差.
- 观察到的偏差和适应模式表明一个反驱动的,类似二进制搜索的重新校准机制.
- 移动范式是一种可扩展和有效的工具,用于评估不同空间环境中的感知认知校准.
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