3,616 responses from 159 respondents to 20 items.
| Description | Retrospective pre-post workshop evaluation (skill/knowledge confidence items, 0-3, Before vs Now as wave) from mentors attending the SCOARE scientific-communication-mentoring workshop across 2 program years |
|---|---|
| Reference | Dahlstrom EK, Bell C, Chang S, Lee HY, Anderson CB, Pham A, et al. (2022) Translating mentoring interventions research into practice: Evaluation of an evidence-based workshop for research mentors on developing trainees' scientific communication skills. PLoS ONE. |
| DOI | 10.1371/journal.pone.0262418 |
| Licence | CC BY 4.0 |
| Source data | https://journals.plos.org/plosone/article/file?type=supplementary&id=10.1371/journal.pone.0262418.s002 |
| Responses | 3,616 |
|---|---|
| Respondents | 159 |
| Items | 20 |
| Response categories | 4 |
| Responses per respondent | 22.742 |
| Responses per item | 180.800 |
| Density | 1.137 |
| Longitudinal | TRUE |
| sample | Program-based |
|---|---|
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | eng |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Evaluation of the SCOARE (Scientific Communication Advances Research Excellence) Workshop post-workshop evaluation survey |
|---|---|
| Mean words per item | 8.250 |
| Mean characters per item | 60.350 |
| Mean characters per response | 3.250 |
| Flesch-Kincaid grade level | 12.157 |
iditemrespwave
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("dahlstrom_2022_scoare")
# Python
pip install irw
import irw
df = irw.fetch("dahlstrom_2022_scoare")
| 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 |