hao_2025_social_regulation

5,200 responses from 650 respondents to 8 items.

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

About this table

DescriptionSocial regulation scale (SR1-8, 8 items, 1-5); foreign language learning; Chinese university students N=650
ReferenceHao et al. (2025). The data about foreign language anxiety. figshare. doi:10.6084/m9.figshare.30397234.v1
LicenceCC BY 4.0
Source datahttps://figshare.com/articles/dataset/The_data_about_foreign_language_anxiety/30397234

Size and shape

Responses5,200
Respondents650
Items8
Response categories5
Responses per respondent8
Responses per item650
Density1
LongitudinalFALSE

Classification

age rangeChild (<18y)
child age (for child-focused studies)Adolescent (12-18y)
sampleEducational
measurement toolSurvey/questionnaire
primary language(s)chi

Item text

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

InstrumentForeign Language Learning Resilience Scale (FLLRS; Guo & Li, 2022), social resilience subscale
Mean words per item18
Mean characters per item111.125
Mean characters per response2
Flesch-Kincaid grade level9.382

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, hao_2025_foreign_language_anxiety.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).NAME
itemIRW standard Item identifier.made in the build script
respIRW standard Response value.made in the build script
Respondent covariates
cov_ageCovariate AGE
cov_regionCovariate REG
cov_sexCovariate SEX

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("hao_2025_social_regulation")
# Python
pip install irw

import irw
df = irw.fetch("hao_2025_social_regulation")

How to cite

@misc{hao2025data,
  author = {Hao et al.},
  title = {The data about foreign language anxiety},
  year = {2025},
  howpublished = {figshare},
  doi = {10.6084/m9.figshare.30397234.v1},
  url = {https://figshare.com/articles/dataset/The_data_about_foreign_language_anxiety/30397234}
}

Version and provenance

IRW versionv569
Redivis datasetitem_response_warehouse_2 v33.0
Redivis dataset DOI10.57761/6m04-m698
Manifest pin for this IRW versionv33.0
Metadata sourceirw_meta v43.0