629,815 responses from 23,282 respondents to 1 items.
| Description | Word-level pronunciation difficulty ratings based on spelling |
|---|---|
| Reference | Edwards, A. A., Rigobon, V. M., Steacy, L. M., & Compton, D. L. (2024). Spelling-to-pronunciation transparency ratings for the 20,000 most frequently written English words. Behavior Research Methods, 56(4), 2828-2841. |
| DOI | 10.3758/s13428-023-02205-2 |
| Licence | CC BY 4.0 |
| Source data | https://github.com/ashleyaedwards/SpellingToPronunciationTransparencyRatings |
| Responses | 629,815 |
|---|---|
| Respondents | 23,282 |
| Items | 1 |
| Response categories | 6 |
| Responses per respondent | 27.052 |
| Responses per item | 629,815 |
| Density | 27.052 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | Educational, Internet-based |
| construct type | Cognitive/educational |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | eng |
| construct name | Word Ratings |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Word-level pronunciation difficulty ratings based on spelling |
|---|---|
| Mean words per item | 1 |
| Mean characters per item | 2 |
| Mean characters per response | 8.167 |
| Flesch-Kincaid grade level | -3.400 |
iditemraterresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("spelling2pronounce_edwards2023")
# Python
pip install irw
import irw
df = irw.fetch("spelling2pronounce_edwards2023")
| IRW version | v393 |
|---|---|
| Redivis dataset | item_response_warehouse v53.0 |
| Redivis dataset DOI | 10.57761/4g08-xt41 |
| Manifest pin for this IRW version | v53.0 |
| Metadata source | irw_meta v23.0 |