37,544 responses from 722 respondents to 52 items.
| Description | 52 vocabulary-learning strategy items (metacognitive, inferencing, dictionary, note-taking, rehearsal, encoding, activation), 1-7. 722 respondents x 52 items = 37544 responses. |
|---|---|
| Reference | Trang, N., Truong, D., & Ha, H. (2023). Quantifying vocabulary learning belief and strategy - A validation study of the Vietnamese version of Gu's (2018) vocabulary learning questionnaire. Heliyon, 9, e16009. https://doi.org/10.1016/j.heliyon.2023.e16009 |
| DOI | 10.1016/j.heliyon.2023.e16009 |
| Licence | CC BY 4.0 |
| Source data | https://europepmc.org/article/PMC/PMC10176061 |
| Responses | 37,544 |
|---|---|
| Respondents | 722 |
| Items | 52 |
| Response categories | 7 |
| Responses per respondent | 52 |
| Responses per item | 722 |
| Density | 1 |
| Longitudinal | FALSE |
| sample | Educational |
|---|---|
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | vie |
cov_genderiditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("trang_2023_vocabulary_strategies")
# Python
pip install irw
import irw
df = irw.fetch("trang_2023_vocabulary_strategies")
| 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 |