matosaslopez_2024_questionnaire_quality

6,669 responses from 2,223 respondents to 3 items.

About this table

DescriptionThree items rating the questionnaire itself (ambiguity, clarity, precision), 1-5. 6,669 responses from 2,223 respondents on 3 items.
ReferenceMatosas-Lopez, L. (2024). Dataset on the evaluation of teaching efficiency comparing Likert-type questionnaires vs BARS [Data set]. Zenodo. https://doi.org/10.5281/zenodo.15151243
LicenceCC BY 4.0
Source datahttps://zenodo.org/records/15151243

Size and shape

Responses6,669
Respondents2,223
Items3
Response categories5
Responses per respondent3
Responses per item2,223
Density1
LongitudinalFALSE

Classification

age rangeAdult (18+)
sampleEducational
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)spa

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, matosaslopez_2024_teacher_assessment.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_ageCovariate Age
cov_genderCovariate Gender
cov_questionnaire_typeCovariate Questionnaire_type
cov_universityCovariate University_Id

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("matosaslopez_2024_questionnaire_quality")
# Python
pip install irw

import irw
df = irw.fetch("matosaslopez_2024_questionnaire_quality")

How to cite

@misc{https://doi.org/10.5281/zenodo.15151243,
  doi = {10.5281/ZENODO.15151243},
  url = {https://zenodo.org/doi/10.5281/zenodo.15151243},
  author = {Matosas-López, Luis},
  keywords = {University, quality, faculty performance, questionnaires, Likert, BARS},
  language = {en},
  title = {Dataset on the evaluation of teaching efficiency comparing Likert-type questionnaires vs BARS-type questionnaires},
  publisher = {Zenodo},
  year = {2024},
  copyright = {Creative Commons Attribution 4.0 International}
}

Version and provenance

IRW versionv566
Redivis datasetitem_response_warehouse_4 v13.0
Redivis dataset DOI10.57761/w8zx-td92
Manifest pin for this IRW versionv13.0
Metadata sourceirw_meta v43.0