an_2020_efl_self_regulated

25,725 responses from 525 respondents to 49 items.

About this table

DescriptionTechnology-based self-regulated English learning strategies scale, Chinese EFL students, 49 items, 1-7, N=525
ReferenceAn, Z., et al. (2020). Profiling Chinese EFL students' technology-based self-regulated English learning strategies. PLOS ONE.
DOI10.1371/journal.pone.0240094
LicenceCC BY 4.0
Source datahttps://journals.plos.org/plosone/article?id=10.1371/journal.pone.0240094

Size and shape

Responses25,725
Respondents525
Items49
Response categories7
Responses per respondent49
Responses per item525
Density1
LongitudinalFALSE

Classification

sampleEducational
measurement toolSurvey/questionnaire
item formatLikert Scale/selected 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.

InstrumentTechnology-based Self-regulated English Learning Strategies Scale (TSELSS) survey battery (Q1-Q26 TSELSS; Q27-Q33 English learning enjoyment/environment items; Q34-Q49 English Language Self-Efficacy Questionnaire)
Mean words per item1.102
Mean characters per item20.061
Mean characters per response2.857
Flesch-Kincaid grade level0.536

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, an_2020_efl_self_regulated.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).index
itemIRW standard Item identifier.made in the build script
respIRW standard Response value.made in the build script
rtIRW standard Response time.totalseconds

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("an_2020_efl_self_regulated")
# Python
pip install irw

import irw
df = irw.fetch("an_2020_efl_self_regulated")

How to cite

@article{An_2020, title={Profiling Chinese EFL students’ technology-based self-regulated English learning strategies}, volume={15}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0240094}, DOI={10.1371/journal.pone.0240094}, number={10}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={An, Zhujun and Gan, Zhengdong and Wang, Chuang}, editor={Xie, Haoran}, year={2020}, month=Oct, pages={e0240094} }

Version and provenance

IRW versionv566
Redivis datasetitem_response_warehouse_3 v13.0
Redivis dataset DOI10.57761/gpg7-sg87
Manifest pin for this IRW versionv13.0
Metadata sourceirw_meta v43.0