gpt4mcq_young_2025

3,800 responses from 190 respondents to 20 items.

About this table

DescriptionChatGPT-4 Multiple-choice item
ReferenceYoung, R., Courtney, E., Kah, A., Wilkerson, M., & Chen, Y.-H. (2025). Content and Item Response Theory Analysis of ChatGPT-4-Generated Multiple-Choice Items. Teaching of Psychology, 0(0). https://doi.org/10.1177/00986283241311220
DOI10.1177/00986283241311220
LicenceCC BY 4.0
Source datahttps://osf.io/zq4eg/?view_only=d78eeb2235e940ca9ae4bb6732fad999

Size and shape

Responses3,800
Respondents190
Items20
Response categories4
Responses per respondent20
Responses per item190
Density1
LongitudinalFALSE

Classification

age rangeAdult (18+)
sampleEducational
construct typeCognitive/educational
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)eng
construct nameChatGPT-4 Multiple-choice item

Item text

This table has item text in the IRW: the wording administered to respondents, not just the response codes.

InstrumentChatGPT-4-generated multiple-choice quiz on the reading 'Love, Friendship, and Social Support'
Mean words per item12.050
Mean characters per item83.650
Mean characters per response58.413
Flesch-Kincaid grade level11.391

Columns

iditemresp

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("gpt4mcq_young_2025")
# Python
pip install irw

import irw
df = irw.fetch("gpt4mcq_young_2025")

Version and provenance

IRW versionv393
Redivis datasetitem_response_warehouse v53.0
Redivis dataset DOI10.57761/4g08-xt41
Manifest pin for this IRW versionv53.0
Metadata sourceirw_meta v23.0