bernik_2026_study_engagement

2,421 responses from 269 respondents to 9 items.

One of 4 tables from the same source; this one measures Study engagement (SE, 9 items). The others are listed under Related tables.

About this table

Description9 study-engagement items (1-5; most likely the UWES-S-9); N = 269 Slovenian university students; cov_gender, cov_age, cov_study_level.
ReferenceBernik, N., Znidarsic, J., Sprajc, P., & Bernik, M. (2026). Excel file containing data from 269 undergraduate and postgraduate students enrolled at Slovenian public universities [data]. figshare. https://doi.org/10.6084/m9.figshare.33307392.v1
LicenceCC BY 4.0
Source datahttps://figshare.com/articles/dataset/_/33307392

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

Responses2,421
Respondents269
Items9
Response categories5
Responses per respondent9
Responses per item269
Density1
LongitudinalFALSE

Classification

age rangeAdult (18+)
sampleEducational
construct typeBehavioral
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)slv
construct nameStudy engagement (SE, 9 items)

Codebook

This codebook is reconstructed by the IRW from the IRW data standard. 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).not traced
itemIRW standard Item identifier.not traced
respIRW standard Response value.not traced
Respondent covariates
cov_ageCovariate not traced
cov_genderCovariate not traced
cov_study_levelCovariate not traced

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("bernik_2026_study_engagement")
# Python
pip install irw

import irw
df = irw.fetch("bernik_2026_study_engagement")

How to cite

@misc{https://doi.org/10.6084/m9.figshare.33307392.v1,
  doi = {10.6084/M9.FIGSHARE.33307392.V1},
  url = {https://figshare.com/articles/dataset/Excel_file_containing_data_from_269_undergraduate_and_postgraduate_students_enrolled_at_Slovenian_public_universities_The_data_were_collected_using_self-report_measures_of_information_and_data_literacy_IDL_academic_self-efficacy_ASE_classro/33307392/1},
  author = {Bernik, Nejc and Žnidaršič, Jasmina and Šprajc, Polona and Bernik, Mojca},
  keywords = {Human resources management, Social psychology, Digital literature, Humanities and social sciences curriculum and pedagogy (excl. economics, business and management)},
  title = {Excel file containing data from 269 undergraduate and postgraduate students enrolled at Slovenian public universities. The data were collected using self-report measures of information and data literacy (IDL), academic self-efficacy (ASE), classroom engagement (CE), and study engagement (SE).},
  publisher = {figshare},
  year = {2026},
  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