11,592 responses from 104 respondents to 63 items.
| Description | 63 digital-competence test items scored 0/1, pre-test (wave 1, 99 students) and post-test (wave 2, 85 students); treat = 1 for the gamification and traditional-teaching arms, 0 for the control; cov_condition names the arm; N = 104 Chilean first-year university students; cov_condition, cov_gender, cov_school_type, cov_school_track, cov_mother_edu, cov_father_edu. |
|---|---|
| Reference | Huentemilla, G., & Manzano Leon, A. (2026). Bata base Gamification versus traditional teaching in the development of digital competence in higher education: A quasi-experimental study [data]. Zenodo. https://doi.org/10.5281/zenodo.22256717 |
| Licence | CC BY 4.0 |
| Source data | https://zenodo.org/records/22256717 |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Responses | 11,592 |
|---|---|
| Respondents | 104 |
| Items | 63 |
| Response categories | 2 |
| Responses per respondent | 111.462 |
| Responses per item | 184 |
| Density | 1.769 |
| Longitudinal | TRUE |
| age range | Adult (18+) |
|---|---|
| sample | Educational |
| construct type | Cognitive/educational |
| measurement tool | Test |
| item format | Likert Scale/selected response |
| primary language(s) | spa |
| construct name | Digital competence knowledge test (63 scored items, pre/post) |
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, huentemilla_2026_digital_competence_test.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.
| Column | What it is | Source column |
|---|---|---|
| IRW standard columns | ||
id | IRW 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 |
item | IRW standard Item identifier. | made in the build script |
resp | IRW standard Response value. | made in the build script |
treat | IRW standard Treatment group assignment in experimental studies. | made in the build script |
wave | IRW standard Longitudinal wave indicator. | made in the build script |
| Respondent covariates | ||
cov_condition | Covariate | made in the build script |
cov_father_edu | Covariate | made in the build script |
cov_gender | Covariate | made in the build script |
cov_mother_edu | Covariate | made in the build script |
cov_school_track | Covariate | made in the build script |
cov_school_type | Covariate | made in the build script |
What item codes and covariate values stand for is in the codebook released with the source data.
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("huentemilla_2026_digital_competence_test")
# Python
pip install irw
import irw
df = irw.fetch("huentemilla_2026_digital_competence_test")
@misc{https://doi.org/10.5281/zenodo.22256717,
doi = {10.5281/ZENODO.22256717},
url = {https://zenodo.org/doi/10.5281/zenodo.22256717},
author = {Huentemilla, Gonzalo and Manzano León, Ana},
title = {Bata base Gamification versus traditional teaching in the development of digital competence in higher education: A quasi-experimental study},
publisher = {Zenodo},
year = {2026},
copyright = {Creative Commons Attribution 4.0 International}
}
| IRW version | v584 |
|---|---|
| Redivis dataset | item_response_warehouse_7 v1.1 |
| Redivis dataset DOI | 10.57761/7pd3-sh31 |
| Manifest pin for this IRW version | v1.0 |
| Metadata source | irw_meta v44.0 |