CSE_Bayazit_2022

9,765 responses from 651 respondents to 15 items.

About this table

DescriptionSelf-Efficacy Scale for Clinical Skills (L-SES)
ReferenceBayazit, A., Gonullu, I., & Dogan, C. D. (2022). Adaptation of a short and universal learning self-efficacy scale for clinical skills in Turkish. Plos one, 17(11), e0275672. Kang, Y. N., Chang, C. H., Kao, C. C., Chen, C. Y., & Wu, C. C. (2019). Development of a short and universal learning self-efficacy scale for clinical skills. PloS one, 14(1), e0209155. BAYAZIT, ALPER, 2022, "Adaptation of a Short and Universal Learning Self-Efficacy Scale for Clinical Skills in Turkish", https://doi.org/10.7910/DVN/M0NJIQ, Harvard Dataverse, V1, UNF:6:RmFV+H/6Bc+ERCX++pcoew== [fileUNF]
LicenceCC0 1.0
Source datahttps://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/M0NJIQ&version=1.0

Size and shape

Responses9,765
Respondents651
Items15
Response categories5
Responses per respondent15
Responses per item651
Density1
LongitudinalFALSE

Classification

age rangeAdult (18+)
sampleEducational
construct typeAffective/mental health
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)tur
construct nameLearning Self-Efficacy Scale (L-SES)

Columns

iditemresp

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("CSE_Bayazit_2022")
# Python
pip install irw

import irw
df = irw.fetch("CSE_Bayazit_2022")

Version and provenance

IRW versionv393
Redivis datasetitem_response_warehouse v53.0
Redivis dataset DOI10.57761/4g08-xt41
Manifest pin for this IRW versionv53.0
Metadata sourceirw_meta v23.0