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最具挑战性项目学习时间分配的难题。

The puzzle of study time allocation for the most challenging items.

机构信息

Department of Psychology, School of Social Sciences, University of Mannheim, Ehrenhof-Ost, 68131, Mannheim, Germany.

Faculty of Industrial Engineering and Management, Technion-Israel Institute of Technology, Haifa, Israel.

出版信息

Psychon Bull Rev. 2017 Dec;24(6):2003-2011. doi: 10.3758/s13423-017-1261-4.

Abstract

Learners often allocate more study time to challenging items than to easier ones. Nevertheless, both predicted and actual memory performance are typically worse for difficult than for easier items. The resulting inverse relations between people's predictions of their memory performance (judgments of learning; JOLs) and self-paced study time (ST) are often explained by bottom-up, data-driven ST allocation that is based on fluency. However, we demonstrate robust inverted U-shaped relations between JOLs and ST that cannot be explained by data-driven ST allocation alone. Consequently, we explored how two models of top-down, strategic ST allocation account for curvilinear JOL-ST relations. First, according to the Region of Proximal Learning model, people stop quickly on items for which they experience too little progress in learning. Second, according to the Diminishing Criterion Model, people set a time limit and stop studying when this time limit is reached. In three experiments, we manipulated motivation with different methods and examined which model best described JOL-ST relations. Consistent with the Diminishing Criterion Model but not with the Region of Proximal Learning model, results revealed that curvilinearity was due to people setting a time limit.

摘要

学习者通常会为具有挑战性的项目分配更多的学习时间,而不是简单的项目。然而,无论是预测的还是实际的记忆表现,通常都是困难的项目比简单的项目差。因此,人们对自己的记忆表现(学习判断;JOL)的预测和自我调整的学习时间(ST)之间的反比关系通常可以用基于流畅性的自下而上、数据驱动的 ST 分配来解释。然而,我们发现 JOL 和 ST 之间存在强大的倒 U 形关系,不能仅用数据驱动的 ST 分配来解释。因此,我们探讨了两种自上而下的策略性 ST 分配模型如何解释曲线形 JOL-ST 关系。首先,根据近端学习区域模型,人们会在学习过程中进展太少的项目上迅速停止。其次,根据衰减标准模型,当达到时间限制时,人们会设定一个时间限制并停止学习。在三个实验中,我们使用不同的方法来操纵动机,并检验哪种模型最能描述 JOL-ST 关系。与衰减标准模型一致,但与近端学习区域模型不一致的是,结果表明,曲线性是由于人们设定了时间限制。

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