Sleep-associated consolidation in app-based language learning
Year: 2020
Type: article
Abstract: Neuro-cognitive models of word learning propose a role for sleep in\nconsolidating new words, yet evidence for sleep-associated memory\nbenefits outside of experimental contexts is scarce. This study\ncompared wake- and sleep-associated memory changes in data from\nMemrise, a publicly available language-learning app. Memory for\nforeign words and phrases remained very high in accuracy across a\n7-12 hour delay, and there were no differences in forgetting between\nwake and sleep. However, learners were quicker to arrive at the\ncorrect translation after a period of sleep compared to wake. This\nsleep-associated benefit was seen for words but not phrases, and\ncould not be fully accounted for by circadian differences in\ncompletion time. As such, we demonstrate that the behavioural\nbenefits of sleep on vocabulary can be observed in real-world\nlanguage learning, and discuss the promise for combining small-\nscale lab studies with naturally occurring datasets to understand\nlearning outcomes.
Author: Emma James
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W3047007741