40,745,825 responses from 637,446 respondents to 4,663 items.
The scored version of this table is choi_2020_ednet_listening.
One of 4 tables from the same source; this one measures TOEIC Listening (EdNet KT1, parts 1-4). The others are listed under Related tables.
| Description | Nominal companion of choi_2020_ednet_listening: EdNet KT1 TOEIC practice answers (Santa / Riiid), parts 1-4; text = the letter picked (a-d), resp = correct. |
|---|---|
| Reference | Choi, Y., Lee, Y., Shin, D., Cho, J., Park, S., Lee, S., Baek, J., Bae, C., Kim, B., & Heo, J. (2020). EdNet: A large-scale hierarchical dataset in education. In Artificial Intelligence in Education (AIED 2020), LNCS 12164, 69-73. |
| DOI | 10.1007/978-3-030-52240-7_13 |
| Licence | CC BY-NC 4.0 |
| Source data | https://github.com/riiid/ednet |
| Responses | 40,745,825 |
|---|---|
| Respondents | 637,446 |
| Items | 4,663 |
| Response categories | 4 |
| Responses per respondent | 63.920 |
| sample | Educational, Internet-based |
|---|---|
| construct type | Cognitive/educational |
| measurement tool | Test |
| item format | Likert Scale/selected response |
| primary language(s) | eng |
| construct name | TOEIC Listening (EdNet KT1, parts 1-4) |
dateiditemitem_familyitemcov_partresprttext
date, id, item, item_family, 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.
Licence: CC BY-NC 4.0 — non-commercial use only.
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("choi_2020_ednet_listening_nom", source = "nom")
# Python
pip install irw
import irw
df = irw.fetch("choi_2020_ednet_listening_nom", source="nom")
@inbook{Choi_2020, title={EdNet: A Large-Scale Hierarchical Dataset in Education}, ISBN={9783030522407}, ISSN={1611-3349}, url={http://dx.doi.org/10.1007/978-3-030-52240-7_13}, DOI={10.1007/978-3-030-52240-7_13}, booktitle={Artificial Intelligence in Education}, publisher={Springer International Publishing}, author={Choi, Youngduck and Lee, Youngnam and Shin, Dongmin and Cho, Junghyun and Park, Seoyon and Lee, Seewoo and Baek, Jineon and Bae, Chan and Kim, Byungsoo and Heo, Jaewe}, year={2020}, pages={69–73} }
| 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 |