23,696 responses from 1,323 respondents to 18 items.
| Description | 18-item Social Adaptability Scale (1-5 scale), from a survey of N=1323 Chinese adolescents on AI in education and social adaptability. |
|---|---|
| Reference | Lai T, Xie C, Ruan M, Wang Z, Lu H, Fu S (2023) Influence of artificial intelligence in education on adolescents' social adaptability: The mediatory role of social support. PLoS ONE. |
| DOI | 10.1371/journal.pone.0283170 |
| Licence | CC BY 4.0 |
| Source data | https://journals.plos.org/plosone/article/file?type=supplementary&id=10.1371/journal.pone.0283170.s001 |
| Responses | 23,696 |
|---|---|
| Respondents | 1,323 |
| Items | 18 |
| Response categories | 5 |
| Responses per respondent | 17.911 |
| Responses per item | 1316.444 |
| Density | 0.995 |
| Longitudinal | FALSE |
| age range | Child (<18y) |
|---|---|
| child age (for child-focused studies) | Child (6-12y), Adolescent (12-18y) |
| sample | Educational |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | chi |
cov_agecov_gendercov_gradecov_schooliditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("lai_2023_social_adaptability")
# Python
pip install irw
import irw
df = irw.fetch("lai_2023_social_adaptability")
| IRW version | v393 |
|---|---|
| Redivis dataset | item_response_warehouse_4 v7.0 |
| Redivis dataset DOI | 10.57761/cpj5-vm97 |
| Manifest pin for this IRW version | v7.0 |
| Metadata source | irw_meta v23.0 |