统计学学习表现受到以前的学习经验的影响: 一项预测性眼动研究
Naama Schwartz1, Louisa Bogaerts2, Yaara Loyfer1
1The Hebrew University of Jerusalem, Israel.
Cognition
|March 8, 2026
概括
统计学学习 (SL) 是由以前的经验塑造的. 从可预测的模式开始有助于新的学习,而不可预测的模式阻碍了它,即使条件后来改善. 学习者积极地对他们的环境形成期望.
科学领域:
- 认知科学 认知科学
- 神经科学是一个神经科学.
- 心理学 心理学 心理学
背景情况:
- 统计学习 (SL) 对认知功能至关重要,但自然环境具有动态的,概率的规律性,与稳定的人工环境不同.
- 了解SL如何适应不断变化的环境和先前经验对于认知理论至关重要.
研究的目的:
- 调查不同可预测性轨迹对SL性能的影响.
- 确定初始学习经验在动态环境中如何影响后续的SL.
主要方法:
- 一个"Whack-a-Mole"游戏被设计成部分可预测的子位置.
- 实验1在两个会议中操纵了可预测性轨迹 (增加然后减少,反之亦然).
- 实验2使用一致的可预测性轨迹 (始终增加或始终减少) 跨会话.
- 通过反应时间和预测性眼动来评估学习.
主要成果:
- 之前的经验在第二次课程中显著塑造了学习.
- 从高可预测性增强学习开始第二次课程.
- 相反,从低可预测性开始阻碍了学习,无论以后可预测性是否增加.
结论:
- 学习者是积极的信息寻找者,而不是被动的接收者,形成影响学习的期望.
- 动态环境中的SL受到环境规律的顺序和历史的深刻影响.
- 结果为SL的理论提供了信息,特别是关于在不断变化的环境中适应和期望形成的理论.
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