asap20train_nom

17,307 responses from 17,307 respondents to 7 items.

About this table

Descriptionargumentative essays from U.S. secondary students
ReferenceCrossley, S. A., Baffour, P., Burleigh, L., & King, J. (2025). A large-scale corpus for assessing source-based writing quality: ASAP 2.0. Assessing Writing, 65, 100954.
DOI10.1016/j.asw.2025.100954
LicenceCC BY 4.0
Source datahttps://github.com/scrosseye/ASAP_2.0/blob/main/ASAP_2_Final_github_train.zip

Size and shape

Responses17,307
Respondents17,307
Items7
Response categories17,307
Responses per respondent1

Columns

cov_economically_disadvantagedcov_ell_statuscov_gendercov_grade_levelcov_race_ethnicitycov_student_disability_statusiditemresptext

Get the data

Download CSVno account neededBrowse on Redivisexplore and queryCroissant metadataHugging Face, Kaggle, OpenML

Or load it directly in R or Python:

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("asap20train_nom", source = "nom")
# Python
pip install irw

import irw
df = irw.fetch("asap20train_nom", source="nom")

How to cite

@article{Crossley_2025, title={A large-scale corpus for assessing source-based writing quality: ASAP 2.0}, volume={65}, ISSN={1075-2935}, url={http://dx.doi.org/10.1016/j.asw.2025.100954}, DOI={10.1016/j.asw.2025.100954}, journal={Assessing Writing}, publisher={Elsevier BV}, author={Crossley, Scott A. and Baffour, Perpetual and Burleigh, L. and King, Jules}, year={2025}, month=July, pages={100954} }

Version and provenance

IRW versionv439
Redivis datasetirw_nominal v2.0
Redivis dataset DOI10.57761/we2p-ym20
Manifest pin for this IRW versionv2.0
Metadata sourceirw_meta v27.0