Finding words in a sea of text: Word search as a measure of sensitivity to statistical regularities in reading

Published on 13th February.

Detalles Bibliográficos
Autores: Isbilen, Erin S, Laver, Abigail, Siegelman, Noam, Magnuson, James S, Aslin, Richard N
Tipo de recurso: artículo
Fecha de publicación:2025
País:España
Institución:Universidad del País Vasco
Repositorio:Addi. Archivo Digital para la Docencia y la Investigación
OAI Identifier:oai:addi.ehu.eus:10810/77439
Acceso en línea:http://hdl.handle.net/10810/77439
Access Level:acceso abierto
Palabra clave:statistical learning
reading
individual differences
literacy
language acquisition
visual search
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spelling Finding words in a sea of text: Word search as a measure of sensitivity to statistical regularities in readingIsbilen, Erin SLaver, AbigailSiegelman, NoamMagnuson, James SAslin, Richard Nstatistical learningreadingindividual differencesliteracylanguage acquisitionvisual searchPublished on 13th February.Statistical learning (SL) is hypothesized to play a fundamental role in reading, yet the correlations between reading and SL are largely mixed. This inconsistency may result from the fact that most SL studies train participants to learn novel, non-linguistic visual regularities, which overlooks two important factors: (a) SL performance varies across domains, and (b) most SL studies utilize tasks with short exposure-phases with a limited set of novel structured stimuli. Rather than exposing participants to novel statistics, we explored how prior learning of the statistical regularities inherent in natural texts predicts individual differences in reading. We developed a novel measure of long-term orthographic SL by assessing participants’ ability to chunk letter information based on its statistical properties. Adults were prompted to find high and low frequency English words (derived from written-language corpora) when a single target word was embedded in an array of background distractors comprising letters that do not form words. Performance on this task was compared against three established measures of component skills of reading: lexical decision, orthographic awareness, and spelling recognition. Participants were faster and more accurate at identifying high frequency words, replicating classic psycholinguistic results. Performance was also impacted by semantic diversity—the variation of the semantic contexts a word appears in— independent of frequency. Critically, word search performance significantly predicted each reading subtest, suggesting that the task draws upon key reading-related skills. Sensitivity to orthographic statistical structure may serve as a crucial foundation that drives individual differences in reading, consistent with SL-based accounts of language.This research was in part supported by a NIH NRSA postdoctoral research grant (F32HD104542) awarded to ESI and a NIH research grant (HD-037082) awarded to Elissa Newport (subcontract to Richard Aslin).APA202620262025info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10810/77439reponame:Addi. Archivo Digital para la Docencia y la Investigacióninstname:Universidad del País VascoIngléshttps://www.apa.org/pubs/journals/xlminfo:eu-repo/semantics/openAccess© 2025 American Psychological Associationoai:addi.ehu.eus:10810/774392026-06-18T09:23:17Z
dc.title.none.fl_str_mv Finding words in a sea of text: Word search as a measure of sensitivity to statistical regularities in reading
title Finding words in a sea of text: Word search as a measure of sensitivity to statistical regularities in reading
spellingShingle Finding words in a sea of text: Word search as a measure of sensitivity to statistical regularities in reading
Isbilen, Erin S
statistical learning
reading
individual differences
literacy
language acquisition
visual search
title_short Finding words in a sea of text: Word search as a measure of sensitivity to statistical regularities in reading
title_full Finding words in a sea of text: Word search as a measure of sensitivity to statistical regularities in reading
title_fullStr Finding words in a sea of text: Word search as a measure of sensitivity to statistical regularities in reading
title_full_unstemmed Finding words in a sea of text: Word search as a measure of sensitivity to statistical regularities in reading
title_sort Finding words in a sea of text: Word search as a measure of sensitivity to statistical regularities in reading
dc.creator.none.fl_str_mv Isbilen, Erin S
Laver, Abigail
Siegelman, Noam
Magnuson, James S
Aslin, Richard N
author Isbilen, Erin S
author_facet Isbilen, Erin S
Laver, Abigail
Siegelman, Noam
Magnuson, James S
Aslin, Richard N
author_role author
author2 Laver, Abigail
Siegelman, Noam
Magnuson, James S
Aslin, Richard N
author2_role author
author
author
author
dc.subject.none.fl_str_mv statistical learning
reading
individual differences
literacy
language acquisition
visual search
topic statistical learning
reading
individual differences
literacy
language acquisition
visual search
description Published on 13th February.
publishDate 2025
dc.date.none.fl_str_mv 2025
2026
2026
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10810/77439
url http://hdl.handle.net/10810/77439
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv https://www.apa.org/pubs/journals/xlm
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
© 2025 American Psychological Association
eu_rights_str_mv openAccess
rights_invalid_str_mv © 2025 American Psychological Association
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv APA
publisher.none.fl_str_mv APA
dc.source.none.fl_str_mv reponame:Addi. Archivo Digital para la Docencia y la Investigación
instname:Universidad del País Vasco
instname_str Universidad del País Vasco
reponame_str Addi. Archivo Digital para la Docencia y la Investigación
collection Addi. Archivo Digital para la Docencia y la Investigación
repository.name.fl_str_mv
repository.mail.fl_str_mv
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