15,594 responses from 15,594 respondents to 15 items.
| Description | Student persuasive writing |
|---|---|
| Reference | Crossley, S., Tian, Y., Baffour, P., Franklin, A., Benner, M., & Boser, U. (2024). A large-scale corpus for assessing written argumentation: PERSUADE 2.0. Assessing Writing, 61, 100865. https://doi.org/10.1016/j.asw.2024.100865 |
| DOI | 10.1016/j.asw.2024.100865 |
| Licence | CC BY 4.0 |
| Source data | https://www.kaggle.com/datasets/julesking/tla-lab-persuade-dataset?select=persuade_train_srctexts.csv |
| Responses | 15,594 |
|---|---|
| Respondents | 15,594 |
| Items | 15 |
| Response categories | 15,594 |
| Responses per respondent | 1 |
cov_economically_disadvantagedcov_ell_statuscov_gendercov_grade_levelcov_race_ethnicitycov_student_disability_statusiditemsource_texttext
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("persuade_learningagency_nom", source = "nom")
# Python
pip install irw
import irw
df = irw.fetch("persuade_learningagency_nom", source="nom")
@article{Crossley_2024, title={A large-scale corpus for assessing written argumentation: PERSUADE 2.0}, volume={61}, ISSN={1075-2935}, url={http://dx.doi.org/10.1016/j.asw.2024.100865}, DOI={10.1016/j.asw.2024.100865}, journal={Assessing Writing}, publisher={Elsevier BV}, author={Crossley, S.A. and Tian, Y. and Baffour, P. and Franklin, A. and Benner, M. and Boser, U.}, year={2024}, month=July, pages={100865} }
| IRW version | v439 |
|---|---|
| Redivis dataset | irw_nominal v2.0 |
| Redivis dataset DOI | 10.57761/we2p-ym20 |
| Manifest pin for this IRW version | v2.0 |
| Metadata source | irw_meta v27.0 |