24,076,951 responses from 118,971 respondents to 27,613 items.
| Description | Items from a dataset from the 2020 NeurIPS Education Challenge, which was used to predict student responses, determine question quality, etc |
|---|---|
| Reference | Wang, Z., Lamb, A., Saveliev, E., Cameron, P., Zaykov, Y., Hernández-Lobato, J.M., Turner, R.E., Baraniuk, R.G., Barton, C., Jones, S.P., Woodhead, S., & Zhang, C. (2020). Diagnostic questions: The neurips 2020 education challenge [data set]. arXiv preprint arXiv:2007.12061 |
| Licence | CC BY 4.0 |
| Source data | https://eedi.com/research#data |
| Responses | 24,076,951 |
|---|---|
| Respondents | 118,971 |
| Items | 27,613 |
| Response categories | 5 |
| Responses per respondent | 202.377 |
| Responses per item | 871.943 |
| Density | 0.007 |
| Longitudinal | FALSE |
| age range | Child (<18y) |
|---|---|
| child age (for child-focused studies) | Child (6-12y), Adolescent (12-18y) |
| sample | Educational |
| construct type | Cognitive/educational |
| measurement tool | Test |
| item format | Likert Scale/selected response |
| primary language(s) | eng |
| construct name | NeurIPS 2020 Education Challenge |
iditemresp
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:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("neurips_2020")
# Python
pip install irw
import irw
df = irw.fetch("neurips_2020")
| 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 |