idcr_martinez_2023_Story_Recall_2

Name: idcr_martinez_2023_Story_Recall_2
Creator: Item Response Warehouse
Published: 2026-09-19
License: CC BY 4.0

10,545 responses from 235 respondents to 48 items.

About this table

Description	Recall based on aural feedback
Reference	Martinez, D. (2024). Scoring story recall for individual differences research: Central details, peripheral details, and automated scoring. Behavior Research Methods, 1-17.
DOI	10.3758/s13428-024-02480-7
Licence	CC BY 4.0
Source data	https://osf.io/5qxkh/

Size and shape

Responses	10,545
Respondents	235
Items	48
Response categories	2
Responses per respondent	44.872
Responses per item	219.688
Density	0.935
Longitudinal	FALSE

Classification

age range	Adult (18+)
sample	Targeted/specific
construct type	Cognitive/educational
measurement tool	Observational rating
item format	Constructed Response
primary language(s)	eng
construct name	Individual differences in story recall

Item text

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

Instrument	Recall based on aural feedback
Mean words per item	2.333
Mean characters per item	13.146
Flesch-Kincaid grade level	31.125

Columns

iditemresp

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:

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("idcr_martinez_2023_Story_Recall_2")

# Python
pip install irw

import irw
df = irw.fetch("idcr_martinez_2023_Story_Recall_2")

Version and provenance

IRW version	v393
Redivis dataset	item_response_warehouse v53.0
Redivis dataset DOI	10.57761/4g08-xt41
Manifest pin for this IRW version	v53.0
Metadata source	irw_meta v23.0