matosaslopez_2022_bars_teaching_inperson

8,880 responses from 888 respondents to 10 items.

About this table

DescriptionStudent evaluation of face-to-face teaching on a 10-item behaviourally-anchored rating scale (BARS), 1-5; classroom behavioural anchors (the 2019 JUTLP instrument). 8,880 responses from 888 students on 10 items.
ReferenceMatosas-Lopez, L. (2022). Datasets on student evaluations of a BARS questionnaire designed for blended-learning and face-to-face teaching [Data set]. Zenodo. https://doi.org/10.5281/zenodo.15151307
LicenceCC BY 4.0
Source datahttps://zenodo.org/records/15151307

Size and shape

Responses8,880
Respondents888
Items10
Response categories5
Responses per respondent10
Responses per item888
Density1
LongitudinalFALSE

Classification

age rangeAdult (18+)
sampleEducational, Program-based
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_2022_bars_teaching.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 edad
cov_genderCovariate género
cov_universityCovariate universidad

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_2022_bars_teaching_inperson")
# Python
pip install irw

import irw
df = irw.fetch("matosaslopez_2022_bars_teaching_inperson")

How to cite

@misc{https://doi.org/10.5281/zenodo.15151307,
  doi = {10.5281/ZENODO.15151307},
  url = {https://zenodo.org/doi/10.5281/zenodo.15151307},
  author = {Matosas-López, Luis},
  keywords = {validity, behavioral episodes, teaching effectiveness, measurement programs, accreditation processes, university},
  language = {es},
  title = {Dataset on student evaluations of a BARS questionnaire designed for face-to-face teaching modalities},
  publisher = {Zenodo},
  year = {2023},
  copyright = {Creative Commons Attribution 4.0 International}
}

Version and provenance

IRW versionv566
Redivis datasetitem_response_warehouse_6 v5.11
Redivis dataset DOI10.57761/qahq-j855
Manifest pin for this IRW versionv5.11
Metadata sourceirw_meta v43.0