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交错学习对类别学习的益处未得到充分重视。

The Underappreciated Benefits of Interleaving for Category Learning.

作者信息

Do Lan Anh, Thomas Ayanna K

机构信息

Department of Psychology, Tufts University, Medford, MA 02155, USA.

出版信息

J Intell. 2023 Aug 2;11(8):153. doi: 10.3390/jintelligence11080153.

Abstract

The present study examined the effects of study schedule (interleaving vs. blocking) and feature descriptions on category learning and metacognitive predictions of learning. Across three experiments, participants studied exemplars from different rock categories and later had to classify novel exemplars. Rule-based and information-based categorization was also manipulated by selecting rock sub-categories for which the optimal strategy was the one that aligned with the extraction of a simple rule, or the one that required integration of information that may be difficult to describe verbally. We observed consistent benefits of interleaving over blocking on rock classification, which generalized to both rule-based (Experiment 1) and information-integration learning (Experiments 1-3). However, providing feature descriptions enhanced classification accuracy only when the stated features were diagnostic of category membership, indicating that their benefits were limited to rule-based learning (Experiment 1) and did not generalize to information-integration learning (Experiments 1-3). Furthermore, our examination of participants' metacognitive predictions demonstrated that participants were not aware of the benefits of interleaving on category learning. Additionally, providing feature descriptions led to higher predictions of categorization even when no significant benefits on actual performance were exhibited.

摘要

本研究考察了学习计划(交错学习与集中学习)和特征描述对类别学习以及学习的元认知预测的影响。在三个实验中,参与者学习了不同岩石类别的示例,随后必须对新的示例进行分类。通过选择岩石子类别来操纵基于规则和基于信息的分类,对于这些子类别,最佳策略要么是与提取简单规则相一致的策略,要么是需要整合可能难以用语言描述的信息的策略。我们观察到,在岩石分类中,交错学习相对于集中学习具有持续的优势,这一优势在基于规则的学习(实验1)和信息整合学习(实验1 - 3)中都得到了体现。然而,只有当所陈述的特征能够诊断类别归属时,提供特征描述才会提高分类准确性,这表明其优势仅限于基于规则的学习(实验1),而没有推广到信息整合学习(实验1 - 3)。此外,我们对参与者元认知预测的考察表明,参与者并未意识到交错学习在类别学习中的优势。另外,即使在实际表现上没有显著益处时,提供特征描述也会导致对分类的更高预测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a4d7/10455486/c566c9e6460b/jintelligence-11-00153-g0A1a.jpg

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