About this table

Description	Human ratings of a divergent thinking measure
Reference	Dumas, D., Organisciak, P., & Doherty, M. (2021). Measuring divergent thinking originality with human raters and text-mining models: A psychometric comparison of methods. Psychology of Aesthetics, Creativity, and the Arts, 15(4), 645.
DOI	10.1037/aca0000319
Licence	CC BY 4.0
Source data	https://osf.io/qcmex/

Size and shape

Responses	21,960
Respondents	92
Items	10
Response categories	5
Responses per respondent	238.696
Responses per item	2,196
Density	23.870
Longitudinal	FALSE

Classification

age range	Mixed
sample	Educational, Targeted/specific
construct type	Cognitive/educational
measurement tool	Survey/questionnaire
item format	Constructed Response
primary language(s)	eng
construct name	Measuring divergent thinking originality with human raters and text-mining models

Item text

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

Mean words per item	1
Mean characters per item	4.700
Mean characters per response	7.400
Flesch-Kincaid grade level	20.430

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, dumas_Organisciak_2022.R. It is our best reading, not the source’s own codebook, and it may contain mistakes. Where the two disagree, the source data are the authority. If you find an error, please tell us.

Column	What it is	Source column
IRW standard columns
`id`	IRW standard Identifier for the focal unit being measured — typically a person, but sometimes another entity (e.g., a word in a lexical task).	`participant`
`item`	IRW standard Item identifier.	`prompt`
`rater`	IRW standard Observer identifier in scenarios where items are rated by an external observer rather than self-reported.	made in the build script
`resp`	IRW standard Response value.	made in the build script
Other columns
`verbatim`	From source Not defined by the IRW standard; the source column’s codebook entry gives its meaning.	`response`

What item codes and covariate values stand for is in the codebook released with the source data.

Get the data

Download CSVno account needed Browse on Redivisexplore and query Croissant metadataHugging Face, Kaggle, OpenML

Or load it directly in R or Python (both need a free Redivis account; the first call opens a browser to sign in):

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("dumas_Organisciak_2022")

# Python
pip install irw

import irw
df = irw.fetch("dumas_Organisciak_2022")

How to cite

@article{Dumas_2021, title={Measuring divergent thinking originality with human raters and text-mining models: A psychometric comparison of methods.}, volume={15}, ISSN={1931-3896}, url={http://dx.doi.org/10.1037/aca0000319}, DOI={10.1037/aca0000319}, number={4}, journal={Psychology of Aesthetics, Creativity, and the Arts}, publisher={American Psychological Association (APA)}, author={Dumas, Denis and Organisciak, Peter and Doherty, Michael}, year={2021}, month=nov, pages={645–663} }

Version and provenance

IRW version	v549
Redivis dataset	item_response_warehouse v70.0
Redivis dataset DOI	10.57761/4qxs-pq87
Manifest pin for this IRW version	v70.0
Metadata source	irw_meta v39.0