509,957 responses from 6,468 respondents to 5,730 items.
| Description | Items from a dataset from the 2022 NeurIPS Education Challenge, is based on real AB experiment data to uncover causal links between learning one construct to the success of learning another |
|---|---|
| Reference | Gong, W., Smith, D., Wang, Z., Barton C., Woodhead, S., Pawlowski, N., Jennings, J., Zhang, C. (2022). NeurIPS Competition Instructions and Guide: Causal Insights for Learning Paths in Education [data set]. arXiv:2208.12610 |
| DOI | 10.48550/arXiv.2208.12610 |
| Licence | CC BY 4.0 |
| Source data | https://eedi.com/research#data |
| Responses | 509,957 |
|---|---|
| Respondents | 6,468 |
| Items | 5,730 |
| Response categories | 2 |
| Responses per respondent | 78.843 |
| Responses per item | 88.998 |
| Density | 0.014 |
| Longitudinal | TRUE |
dateiditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("neurips_2022")
# Python
pip install irw
import irw
df = irw.fetch("neurips_2022")
| 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 |