Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Long-term associative learning predicts verbal short-term memory performance

Jones, Gary and Macken, William ORCID: https://orcid.org/0000-0003-2928-656X 2018. Long-term associative learning predicts verbal short-term memory performance. Memory and Cognition 46 (2) , pp. 216-229. 10.3758/s13421-017-0759-3

[thumbnail of Macken. Long term assocaitive (gold).pdf]
Preview
PDF - Published Version
Download (564kB) | Preview

Abstract

Studies using tests such as digit span and nonword repetition have implicated short-term memory across a range of developmental domains. Such tests ostensibly assess specialized processes for the short-term manipulation and maintenance of information that are often argued to enable long-term learning. However, there is considerable evidence for an influence of long-term linguistic learning on performance in short-term memory tasks that brings into question the role of a specialized short-term memory system separate from long-term knowledge. Using natural language corpora, we show experimentally and computationally that performance on three widely used measures of short-term memory (digit span, nonword repetition, and sentence recall) can be predicted from simple associative learning operating on the linguistic environment to which a typical child may have been exposed. The findings support the broad view that short-term verbal memory performance reflects the application of long-term language knowledge to the experimental setting.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Psychology
Publisher: Psychonomic Society
ISSN: 0090-502X
Date of First Compliant Deposit: 19 September 2017
Date of Acceptance: 18 September 2017
Last Modified: 06 May 2023 07:24
URI: https://orca.cardiff.ac.uk/id/eprint/104769

Citation Data

Cited 7 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics