162 responses from 27 respondents to 6 items.
| Description | NASA Task Load Index (NASA-TLX), robot-programming curricula study, 6 items, 1-5, N=27 |
|---|---|
| Reference | Ajaykumar, G., et al. (2023). Curricula for teaching end-users to kinesthetically program collaborative robots. PLOS ONE. |
| DOI | 10.1371/journal.pone.0294786 |
| Licence | CC BY 4.0 |
| Source data | https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0294786 |
| Responses | 162 |
|---|---|
| Respondents | 27 |
| Items | 6 |
| Response categories | 5 |
| Responses per respondent | 6 |
| Responses per item | 27 |
| Density | 1 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | Educational |
| construct type | Other |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | eng |
| construct name | Adapted NASA Task Load Index (NASA-TLX) |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | NASA Task Load Index (NASA-TLX) -- the study administered a modified version, adapted to 5-point Likert scales |
|---|---|
| Mean words per item | 27.167 |
| Mean characters per item | 178.833 |
| Mean characters per response | 4.600 |
| Flesch-Kincaid grade level | 11.544 |
cov_conditioniditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("ajaykumar_2023_nasa_tlx")
# Python
pip install irw
import irw
df = irw.fetch("ajaykumar_2023_nasa_tlx")
| IRW version | v393 |
|---|---|
| Redivis dataset | item_response_warehouse_3 v7.0 |
| Redivis dataset DOI | 10.57761/pqqn-pm43 |
| Manifest pin for this IRW version | v7.0 |
| Metadata source | irw_meta v23.0 |