1,166 responses from 402 respondents to 3 items.
One of 5 tables from the same source; this one is the intent_career table. The others are listed under Related tables.
| Description | Intent to immediately join tourism career (3 items 6-pt Likert) N=402 Hong Kong students |
|---|---|
| Reference | Choy MW et al. (2022) Career choice of tourism students in a triple-whammy crisis. PLOS ONE. |
| DOI | 10.1371/journal.pone.0279411 |
| Licence | CC BY 4.0 |
| Source data | https://journals.plos.org/plosone/article/file?type=supplementary&id=10.1371/journal.pone.0279411.s001 |
| Responses | 1,166 |
|---|---|
| Respondents | 402 |
| Items | 3 |
| Response categories | 6 |
| Responses per respondent | 2.900 |
| Responses per item | 388.667 |
| Density | 0.967 |
| Longitudinal | FALSE |
| sample | Educational |
|---|---|
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | eng, chi |
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, choy_2022_career_choice.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). | made in the build script |
item | IRW standard Item identifier. | made in the build script |
resp | IRW standard Response value. | made in the build script |
| Respondent covariates | ||
cov_age | Covariate | age |
cov_gender | Covariate | gender |
cov_hotel_discipline | Covariate | hotel |
cov_program | Covariate | program |
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:
# R (no account needed)
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("choy_2022_intent_career")
# Python (needs a free Redivis account)
pip install irw
import irw
df = irw.fetch("choy_2022_intent_career")
@article{Choy_2022, title={Career choice of tourism students in a triple-whammy crisis}, volume={17}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0279411}, DOI={10.1371/journal.pone.0279411}, number={12}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Choy, Monica Waichun and Yeung, Alexander Seeshing}, editor={Wut, Tai Ming}, year={2022}, month=Dec, pages={e0279411} }
| IRW version | v540 |
|---|---|
| Redivis dataset | item_response_warehouse_3 v13.0 |
| Redivis dataset DOI | 10.57761/gpg7-sg87 |
| Manifest pin for this IRW version | v13.0 |
| Metadata source | irw_meta v37.0 |