meng_2017_referent_assignment

1,480 responses from 74 respondents to 5 items.

About this table

Description5 raw explicit/ambiguous-question referent-assignment correctness scores per trial (74 children x 4 trials, wave-coded)
ReferenceMeng X, Murakami T, Hashiya K (2017). Phonological loop affects children's interpretations of explicit but not ambiguous questions: Research on links between working memory and referent assignment. PLOS ONE, 12(10), e0187368. https://doi.org/10.1371/journal.pone.0187368
DOI10.1371/journal.pone.0187368
LicenceCC BY 4.0
Source datahttps://doi.org/10.1371/journal.pone.0187368.s001

Size and shape

Responses1,480
Respondents74
Items5
Response categories2
Responses per respondent20
Responses per item296
Density4
LongitudinalTRUE

Classification

sampleEducational
measurement toolTest
item formatConstructed Response
primary language(s)chi

Item text

This table has item text in the IRW: the wording administered to respondents, not just the response codes.

InstrumentReference assignment task (Murakami & Hashiya, 2014)
Mean words per item8.200
Mean characters per item49.200
Mean characters per response8
Flesch-Kincaid grade level1.092

Columns

cov_age_monthscov_cescov_lpscov_patterncov_sexiditemrespwave

Get the data

Download CSVno account neededBrowse on Redivisexplore and queryCroissant metadataHugging Face, Kaggle, OpenML

Or load it directly in R or Python:

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("meng_2017_referent_assignment")
# Python
pip install irw

import irw
df = irw.fetch("meng_2017_referent_assignment")

Version and provenance

IRW versionv393
Redivis datasetitem_response_warehouse_3 v7.0
Redivis dataset DOI10.57761/pqqn-pm43
Manifest pin for this IRW versionv7.0
Metadata sourceirw_meta v23.0