357,601 responses from 1,053 respondents to 12,276 items.
| Description | Modeling of second language acquisition, data from French learners (who already speak English). |
|---|---|
| Reference | Settles, Burr, 2018, "Data for the 2018 Duolingo Shared Task on Second Language Acquisition Modeling (SLAM)", https://doi.org/10.7910/DVN/8SWHNO, Harvard Dataverse, V4, https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/8SWHNO |
| Licence | CC BY 4.0 |
| Source data | http://sharedtask.duolingo.com/2018.html#task-definition-data |
| Responses | 357,601 |
|---|---|
| Respondents | 1,053 |
| Items | 12,276 |
| Response categories | 2 |
| Responses per respondent | 339.602 |
| Responses per item | 29.130 |
| Density | 0.028 |
| Longitudinal | FALSE |
| sample | General/non-specific |
|---|---|
| construct type | Cognitive/educational |
| measurement tool | Test |
| item format | Constructed Response |
| primary language(s) | eng, fre |
| construct name | reverse_tap |
dependency_headdependency_labelformatiditemmorphologypart_speechresprtsessionstem
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("duolingo_fr_en__reverse_tap")
# Python
pip install irw
import irw
df = irw.fetch("duolingo_fr_en__reverse_tap")
| IRW version | v393 |
|---|---|
| Redivis dataset | item_response_warehouse v53.0 |
| Redivis dataset DOI | 10.57761/4g08-xt41 |
| Manifest pin for this IRW version | v53.0 |
| Metadata source | irw_meta v23.0 |