128 responses from 32 respondents to 4 items.
| Description | Vignette-based decision-quality indicators, binary (1=best-practice choice); N=32, 4 items, K-12/adult ML instructors |
|---|---|
| Reference | Chowdhury, S., & Sain, N. (2026). Teacher AI Literacy for ML Learner Instruction. figshare. |
| Licence | CC BY 4.0 |
| Source data | https://figshare.com/articles/dataset/Teacher_AI_Literacy_for_ML_Learner_Instruction/31427369 |
| Responses | 128 |
|---|---|
| Respondents | 32 |
| Items | 4 |
| Response categories | 2 |
| Responses per respondent | 4 |
| Responses per item | 32 |
| Density | 1 |
| Longitudinal | FALSE |
| sample | Workplace |
|---|---|
| measurement tool | Survey/questionnaire |
cov_ai_policy_existscov_ml_percentcov_prior_ai_pdcov_rolecov_teaches_mlcov_years_teachingiditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("chowdhury2026_ai_vignette")
# Python
pip install irw
import irw
df = irw.fetch("chowdhury2026_ai_vignette")
| IRW version | v393 |
|---|---|
| Redivis dataset | item_response_warehouse_3 v7.0 |
| Redivis dataset DOI | 10.57761/pqqn-pm43 |
| Manifest pin for this IRW version | v7.0 |
| Metadata source | irw_meta v23.0 |