golzar_2024_teacher_burnout

4,312 responses from 196 respondents to 22 items.

One of 4 tables from the same source; this one measures Teacher burnout (22-item MBI-Educators form). The others are listed under Related tables.

About this table

Description22 burnout items (1-5), a Maslach Burnout Inventory-Educators form (the authors' EE/DP/RPA means); N = 196 teachers (country and language not stated in the deposit).
ReferenceGolzar, J. (2024). SPSS File for Teachers' Grit, Self-efficacy, Motivation and Burnout [data]. figshare. https://doi.org/10.6084/m9.figshare.28052750.v1
LicenceCC BY 4.0
Source datahttps://figshare.com/articles/dataset/SPSS_File_for_Teachers_Grit_Self-efficacy_Motivation_and_Burnout/28052750

Notes

These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.

Size and shape

Responses4,312
Respondents196
Items22
Response categories5
Responses per respondent22
Responses per item196
Density1
LongitudinalFALSE

Classification

age rangeAdult (18+)
sampleEducational, Workplace
construct typeAffective/mental health
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)eng
construct nameTeacher burnout (22-item MBI-Educators form)

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, golzar_2024_teacher_burnout.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

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("golzar_2024_teacher_burnout")
# Python
pip install irw

import irw
df = irw.fetch("golzar_2024_teacher_burnout")

How to cite

@misc{https://doi.org/10.6084/m9.figshare.28052750.v1,
  doi = {10.6084/M9.FIGSHARE.28052750.V1},
  url = {https://figshare.com/articles/dataset/SPSS_File_for_Teachers_Grit_Self-efficacy_Motivation_and_Burnout/28052750/1},
  author = {Golzar, Jawad},
  keywords = {Educational psychology, Other education not elsewhere classified},
  title = {SPSS File for Teachers' Grit, Self-efficacy, Motivation and Burnout},
  publisher = {figshare},
  year = {2024},
  copyright = {Creative Commons Attribution 4.0 International}
}

Version and provenance

IRW versionv584
Redivis datasetitem_response_warehouse_7 v1.1
Redivis dataset DOI10.57761/7pd3-sh31
Manifest pin for this IRW versionv1.0
Metadata sourceirw_meta v44.0