dahlstrom_2022_scoare

3,616 responses from 159 respondents to 20 items.

About this table

DescriptionRetrospective 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
ReferenceDahlstrom 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.
DOI10.1371/journal.pone.0262418
LicenceCC BY 4.0
Source datahttps://journals.plos.org/plosone/article/file?type=supplementary&id=10.1371/journal.pone.0262418.s002

Size and shape

Responses3,616
Respondents159
Items20
Response categories4
Responses per respondent22.742
Responses per item180.800
Density1.137
LongitudinalTRUE

Classification

sampleProgram-based
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)eng

Item text

This table has item text in the IRW: the wording administered to respondents, not just the response codes.

InstrumentEvaluation of the SCOARE (Scientific Communication Advances Research Excellence) Workshop post-workshop evaluation survey
Mean words per item8.250
Mean characters per item60.350
Mean characters per response3.250
Flesch-Kincaid grade level12.157

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, dahlstrom_2022_scoare.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.

ColumnWhat it isSource column
IRW standard columns
idIRW standard Identifier for the focal unit being measured — typically a person, but sometimes another entity (e.g., a word in a lexical task).ID
itemIRW standard Item identifier.made in the build script
respIRW standard Response value.made in the build script
waveIRW standard Longitudinal wave indicator.made in the build script

What item codes and covariate values stand for is in the codebook released with the source data.

Get the data

Download CSVno account neededBrowse on Redivisexplore and queryCroissant metadataHugging Face, Kaggle, OpenML

Or load it directly in R or Python (both need a free Redivis account; the first call opens a browser to sign in):

# 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")

How to cite

@article{Dahlstrom_2022, title={Translating mentoring interventions research into practice: Evaluation of an evidence-based workshop for research mentors on developing trainees’ scientific communication skills}, volume={17}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0262418}, DOI={10.1371/journal.pone.0262418}, number={2}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Dahlstrom, Erin K. and Bell, Christine and Chang, Shine and Lee, Hwa Young and Anderson, Cheryl B. and Pham, Annie and Pribbenow, Christine Maidl and Cameron, Carrie A.}, editor={Smith, Dawn K.}, year={2022}, month=Feb, pages={e0262418} }

Version and provenance

IRW versionv557
Redivis datasetitem_response_warehouse_3 v13.0
Redivis dataset DOI10.57761/gpg7-sg87
Manifest pin for this IRW versionv13.0
Metadata sourceirw_meta v40.0