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探索关键的眼球追踪指标,以识别雷文的高级渐进矩阵中的认知策略:数据驱动的视角

Yaohui Liu^1,2, Keren He³, Kaiwen Man⁴

¹School of Psychology, Zhejiang Normal University, Jinhua 321004, China.

Journal of Intelligence

|February 25, 2025

概括

像比例时间矩阵 (PTM) 这样的眼睛跟踪指标显著预测了乌在认知策略的使用.

科学领域:

认知心理学认知心理学
人与计算机的互动.
神经科学是一个神经科学.

背景情况:

在复杂的推理任务中理解认知策略至关重要.
准确性和响应时间等传统措施提供有限的洞察力.
眼睛追踪为客观认知评估提供了一个有前途的途径.

研究的目的:

识别关键特征,包括眼睛跟踪指标,可以预测认知策略的使用.
为此目的,评估递归特征消除和随机森林算法的有效性.
验证识别特征在区分认知策略中的实用性.

主要方法:

使用随机森林算法使用递归特征消除.
分析的项目响应精度 (RA),响应时间 (RT) 和五个眼睛跟踪指标:矩阵上的比例时间 (PTM),第一个切换的延迟 (LFT),第一个切换的延迟率 (RLT),切换次数 (NOT) 和切换率 (ROT).
利用对最佳特征的聚类分析来验证战略差异化.

主要成果:

矩阵上的比例时间 (PTM),延迟到第一次切换的速度 (RLT) 和延迟到第一次切换 (LFT) 是最关键的预测因素.
最强的预测因素是PTM,其次是RLT和LFT.
聚类分析证实了这些特征在区分认知策略方面的实用性.

结论:

特定的眼睛跟踪指标可以作为复杂推理过程中认知处理的客观指标.
这种数据驱动的方法有效地识别了认知策略.
这些发现支持将眼睛跟踪纳入认知策略研究.

关键词:

认知战略是一种认知策略.眼睛的运动眼睛的运动情报情报情报的情报情报的情报.矩阵推理是一种矩阵推理.随机的森林随机的森林

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