liu_2022_fragreading_cdq

10,076 responses from 916 respondents to 11 items.

About this table

Description11-item Cognitive Development Questionnaire (5-point Likert), same n=916 Chinese university student sample as liu_2022_fragreading_frq
ReferenceLiu W, Huang H, Saleem A, Zhao Z (2022). The effects of university students' fragmented reading on cognitive development in the new media age: evidence from Chinese higher education. PeerJ.
DOI10.7717/peerj.13861
LicenceCC BY 4.0
Source datahttps://europepmc.org/article/PMC/PMC9415515

Size and shape

Responses10,076
Respondents916
Items11
Response categories5
Responses per respondent11
Responses per item916
Density1
LongitudinalFALSE

Classification

age rangeAdult (18+)
sampleEducational
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)chi

Item text

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

InstrumentCognitive Development Questionnaire (Section III of the Questionnaire on the new media reading behavior of university students)
Mean words per item13.455
Mean characters per item73.909
Mean characters per response4
Flesch-Kincaid grade level8.394

Columns

cov_agecov_c6cov_c7cov_degree_levelcov_gendercov_gradecov_majoriditemresp

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("liu_2022_fragreading_cdq")
# Python
pip install irw

import irw
df = irw.fetch("liu_2022_fragreading_cdq")

Version and provenance

IRW versionv393
Redivis datasetitem_response_warehouse_4 v7.0
Redivis dataset DOI10.57761/cpj5-vm97
Manifest pin for this IRW versionv7.0
Metadata sourceirw_meta v23.0