14,289 responses from 202 respondents to 3,719 items.
One of 2 tables from the same source; this one measures Creative quality ratings from 3 raters for individual creative ideas generated in the Alternate Uses Task.. The others are listed under Related tables.
| Description | Creative quality ratings from 3 raters for individual creative ideas generated in the Alternate Uses Task. |
|---|---|
| Reference | Forthmann, Boris, and Nils Myszkowski. 2024. “Analysis of a Divergent Thinking Dataset.” OSF. April 22. osf.io/a9qnc. |
| Licence | CC BY 4.0 |
| Source data | https://osf.io/a9qnc/overview |
| Responses | 14,289 |
|---|---|
| Respondents | 202 |
| Items | 3,719 |
| Response categories | 5 |
| Responses per respondent | 70.738 |
| Responses per item | 3.842 |
| Density | 0.019 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | Educational, Targeted/specific |
| construct type | Behavioral, Cognitive/educational |
| measurement tool | Observational rating |
| item format | Mixed |
| primary language(s) | eng |
| construct name | Creative quality ratings from 3 raters for individual creative ideas generated in the Alternate Uses Task. |
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, forthmann-2024.py. 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). | subject_id |
item | IRW standard Item identifier. | made in the build script |
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 |
| Respondent covariates | ||
cov_age | Covariate | made in the build script |
cov_aggression | Covariate | made in the build script |
cov_conventionalism | Covariate | made in the build script |
cov_flu_animals | Covariate | made in the build script |
cov_flu_letterf | Covariate | made in the build script |
cov_flu_letters | Covariate | made in the build script |
cov_flu_super | Covariate | made in the build script |
cov_object | Covariate | made in the build script |
cov_rwa | Covariate | made in the build script |
cov_sex | Covariate | made in the build script |
cov_submission_r | Covariate | made in the build script |
cov_ts | Covariate | made in the build script |
cov_vf_flu | Covariate | made in the build script |
| Other columns | ||
itemcov_frequency | Not documented Covariates invariant to measurement probes (item-level attributes). | made in the build script |
itemcov_idea_type | Not documented Covariates invariant to measurement probes (item-level attributes). | made in the build script |
What item codes and covariate values stand for is in the codebook released with the source data.
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("Forthmann-2024-creative_quality")
# Python
pip install irw
import irw
df = irw.fetch("Forthmann-2024-creative_quality")
@misc{Forthmann2024,
author = {Boris Forthmann and Nils Myszkowski},
title = {Analysis of a Divergent Thinking Dataset},
year = {2024},
howpublished = {\url{https://osf.io/a9qnc/overview}},
note = {OSF, April 22},
url = {https://osf.io/a9qnc/overview}
}
| IRW version | v566 |
|---|---|
| Redivis dataset | item_response_warehouse_2 v33.0 |
| Redivis dataset DOI | 10.57761/6m04-m698 |
| Manifest pin for this IRW version | v33.0 |
| Metadata source | irw_meta v43.0 |