10,087,305 responses from 91,331 respondents to 1,458 items.
The scored version of this table is geography.
One of 2 tables from the same source. The others are listed under Related tables.
| Description | Nominal companion of geography (slepemapy.cz adaptive geography practice, 2012-2015): 10.1M answers, 91,331 learners, 1,458 places; text = id of the place chosen, or dont_know; options offered in trial_options, place names in itemcov_place_name. |
|---|---|
| Reference | Papoušek, J., Pelánek, R., & Stanislav, V. (2016). Adaptive geography practice data set. Journal of Learning Analytics, 3(2), 317-321. |
| DOI | 10.18608/jla.2016.32.17 |
| Licence | ODbL 1.0 |
| Source data | https://www.fi.muni.cz/adaptivelearning/data/slepemapy/ |
| Responses | 10,087,305 |
|---|---|
| Respondents | 91,331 |
| Items | 1,458 |
| Response categories | 1,455 |
| Responses per respondent | 110.448 |
dateiditemitemcov_place_nameitemcov_place_typeresprttexttrial_maptrial_optionstrial_type
date, id, item, resp, rt are defined in the IRW data standard and mean the same in every table. For the other columns, including what item codes and covariate values stand for, any codebook is the one released with the source data.
This table is larger than Redivis serves without a login, so download it with one of the packages below or while signed in to Redivis.
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("geography_nom", source = "nom")
# Python
pip install irw
import irw
df = irw.fetch("geography_nom", source="nom")
@article{Papou_ek_2016, title={Adaptive Geography Practice Data Set}, volume={3}, ISSN={1929-7750}, url={http://dx.doi.org/10.18608/jla.2016.32.17}, DOI={10.18608/jla.2016.32.17}, number={2}, journal={Journal of Learning Analytics}, publisher={Society for Learning Analytics Research}, author={Papoušek, Jan and Pelánek, Radek and Stanislav, Vít}, year={2016}, month=Sept, pages={317–321} }
| IRW version | v581 |
|---|---|
| Redivis dataset | irw_nominal v4.1 |
| Redivis dataset DOI | 10.57761/9hzd-dc70 |
| Manifest pin for this IRW version | v4.1 |
| Metadata source | irw_meta v44.0 |