chanal_2020_francais

18,879 responses from 576 respondents to 33 items.

One of 5 tables from the same source; this one is the francais table. The others are listed under Related tables.

About this table

Description33-item French-language domain self-concept scale, French school-subject-specificity study
ReferenceChanal J, Paumier D (2020) The school-subject-specificity hypothesis and the multidimensionality of academic self-concept: An investigation with a French sample. PLOS ONE
DOI10.1371/journal.pone.0230103
LicenceCC BY 4.0
Source datahttps://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0230103.s001&type=supplementary

Size and shape

Responses18,879
Respondents576
Items33
Response categories7
Responses per respondent32.776
Responses per item572.091
Density0.993
LongitudinalFALSE

Classification

sampleEducational
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)fre

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, chanal_2020_selfconcept.py. It is our best reading, not the source’s own codebook, and it may contain mistakes. Where the two disagree, the source data are the authority. If you find an error, please tell us.

ColumnWhat it isSource column
IRW standard columns
idIRW standard Identifier for the focal unit being measured — typically a person, but sometimes another entity (e.g., a word in a lexical task).made in the build script
itemIRW standard Item identifier.made in the build script
respIRW standard Response value.made in the build script
Respondent covariates
cov_genderCovariate made in the build script

What item codes and covariate values stand for is in the codebook released with the source data.

Get the data

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

Or load it directly in R or Python (both need a free Redivis account; the first call opens a browser to sign in):

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("chanal_2020_francais")
# Python
pip install irw

import irw
df = irw.fetch("chanal_2020_francais")

How to cite

@article{Chanal_2020, title={The school-subject-specificity hypothesis: Implication in the relationship with grades}, volume={15}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0230103}, DOI={10.1371/journal.pone.0230103}, number={4}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Chanal, Julien and Paumier, Delphine}, editor={Ngu, Bing Hiong}, year={2020}, month=Apr, pages={e0230103} }

Version and provenance

IRW versionv557
Redivis datasetitem_response_warehouse_4 v13.0
Redivis dataset DOI10.57761/w8zx-td92
Manifest pin for this IRW versionv13.0
Metadata sourceirw_meta v40.0