Evidence map›Paper›PMID 37743565›Full record

ArticleDevelopmental science2024

Statistical learning and children's emergent literacy in rural Côte d'Ivoire.

Benjamin D Zinszer, Joelle Hannon, Anqi Hu, Aya Élise Kouadio, Hermann Akpé, Fabrice Tanoh, Madeleine Wang, Zhenghan Qi, Kaja Jasińska

Abstract read
In one paragraph

Article in Developmental science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Benjamin D ZinszerDepartment of Psychology, Swarthmore College, Swarthmore, Pennsylvania, USA.ORCID 0000-0002-4568-3568
Joelle HannonDepartment of Linguistics and Cognitive Science, University of Delaware, Newark, Delaware, USA.
Anqi HuDepartment of Linguistics and Cognitive Science, University of Delaware, Newark, Delaware, USA.
Aya Élise KouadioUFR Sciences de l'Homme et de la Société, Université Félix Houphouët-Boigny, Abidjan, Côte d'Ivoire.
Hermann AkpéUFR Sciences de l'Homme et de la Société, Université Félix Houphouët-Boigny, Abidjan, Côte d'Ivoire.
Fabrice TanohUFR Sciences de l'Homme et de la Société, Université Félix Houphouët-Boigny, Abidjan, Côte d'Ivoire.
Madeleine WangDepartment of Psychology, Swarthmore College, Swarthmore, Pennsylvania, USA.
Zhenghan QiDepartment of Communication Sciences and Disorders, Northeastern University, Boston, Massachusetts, USA.
Kaja JasińskaHaskins Laboratories, New Haven, Connecticut, USA.ORCID 0000-0002-8851-1627

Funding

The role of statistical learning in the atypical language development in ASDR21DC017576 · NIDCD · UNIVERSITY OF DELAWARE · PI QI, ZHENGHAN · 2019 to 2022
$547k
Eugene M. Lang Summer Research Fellowship (Swarthmore College)Jacobs Foundation Early Career Award 2015118455Language Learning Registered Reports by Early Career Researchers GrantNational Alliance for Research on Schizophrenia and Depression Young Investigator Award 24836NIDCD NIH HHS R21 DC017576NIDCD NIH HHS R21DC017576Swarthmore College Department of PsychologyTRECC Program training grant 2015-1184
6 · The paper itself

Abstract

Studies of non-linguistic statistical learning (SL) have often linked performance in SL tasks with differences in language outcomes. Most of these studies have focused on Western and high-income educational contexts, but children worldwide learn in radically different educational systems and communities, and often in a second language. In the west African nation of Côte d'Ivoire, children enter fifth grade (CM-1) with widely varying ages and literacy skills. Across three iteratively-developed experiments, 157 children, age 8-15 years, in rural communities in the greater-Adzópe region of Côte d'Ivoire watched sequences of cartoon images with embedded triplet patterns on touchscreen tablets, while performing a target-detection task. We assessed these tablet-based adaptations of non-linguistic visual SL and asked whether the children's individual differences in performance on the SL tasks were related to their first and second language and literacy skills. We found group-level evidence that children used the statistical regularities in the image sequence to gradually decrease their response times, but their responses on post-test discrimination did not reflect this learning. When evaluating the correlation between SL and language skills, individual differences related to other task demands predicted oral language skills shared by first and second languages, while SL better predicted second language print skills. These findings suggest that non-linguistic SL paradigms can measure similar skills in Ivorian children as previous samples, but they also echo recent calls for further cross-cultural validation, greater internal reliability, and tests for confounding variables (such as processing speed) in studies of individual differences in statistical learning. RESEARCH HIGHLIGHTS: We iteratively adapted three visual statistical learning studies for children in rural Côte d'Ivoire. Group-level analyses indicates that the children learn the underlying statistical regularities. Individual-differences analyses reveal some evidence that the statistical learning measure is also correlated with task demands that may be driven by cross-cultural differences. Like previous research, statistical learning is correlated with second language literacy, but we did not find a relationship between SL and oral language skills in first and second languages.

Indexed as

LiteracyRural PopulationAdolescentChildCote d'IvoireFemaleHumansLanguageLanguage DevelopmentLearningMalebilingualismCôte d'Ivoireeducationemergent literacystatistical learning

Identifiers

PMID37743565
PMCPMC10960734

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.