ArticleLanguage learning2021
Desirable Difficulties in Language Learning? How Talker Variability Impacts Artificial Grammar Learning.
Article in Language learning, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- ENIGMA: A Web Application for Running Online Artificial Grammar Learning Experiments.Journal of psycholinguistic research · 2024Article
- Talker variability is not always the right noise: 14 month olds struggle to learn dissimilar word-object pairs under talker variability conditions.Journal of experimental child psychology · 2023Article
- Talker variability shapes early word representations in English-learning 8-month-olds.Infancy : the official journal of the International Society on Infant Studies · 2022Article
- Desirable Difficulties in Language Learning? How Talker Variability Impacts Artificial Grammar Learning.Language learning · 2021Article
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Authors and funding
2 authors.
Funding
Abstract
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.
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Registered trials
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