Desirable Difficulties in Language Learning? How Talker Variability Impacts Artificial Grammar Learning,Language Learning

当前位置： X-MOL 学术 › Lang. Learn. › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

Desirable Difficulties in Language Learning? How Talker Variability Impacts Artificial Grammar Learning
Language Learning ( IF 3.5 ) Pub Date : 2021-07-10 , DOI: 10.1111/lang.12464
Federica Bulgarelli _{1,

2} , Daniel J Weiss ₂

Affiliation

Contending with talker variability has been found to lead to processing costs but also benefits by focusing learners on invariant properties of the signal, indicating that talker variability acts as a desirable difficulty. That is, talker variability may lead to initial costs followed by long-term benefits for retention and generalization. Adult participants learned an artificial grammar affording learning of multiple components in two experiments varying in difficulty. They learned from one, two, or eight talkers and were tested at three time points. The eight-talker condition did not impact learning. The two-talker condition negatively impacted some aspects of learning, but only under more difficult conditions. Generalization of the grammatical dependency was difficult. Thus, we discovered that high and limited talker variability can differentially impact artificial grammar learning. However, talker variability did not act as a desirable difficulty in the current paradigm as the few evidenced costs were not related to long-term benefits.

中文翻译：

语言学习中理想的困难是什么？说话者的变异性如何影响人工语法学习

人们发现，与说话者的可变性进行斗争会导致处理成本，但通过让学习者关注信号的不变属性也有好处，这表明说话者的可变性是一个理想的困难。也就是说，说话者的可变性可能会导致初始成本，然后带来保留和泛化的长期好处。成人参与者学习了人工语法，在两个难度不同的实验中学习多个组件。他们向一名、两名或八名谈话者学习，并在三个时间点进行测试。八人说话的情况并不影响学习。两个人说话的情况对学习的某些方面产生了负面影响，但仅限于更困难的条件下。语法依赖性的概括很困难。因此，我们发现说话者的高变异性和有限变异性会对人工语法学习产生不同的影响。然而，在当前范式中，说话者的可变性并没有成为一个理想的困难，因为少数证据表明的成本与长期利益无关。

更新日期：2021-07-10

点击分享查看原文

点击收藏

阅读更多本刊最新论文