makransky_2016_self_efficacy

2,808 responses from 189 respondents to 8 items.

About this table

DescriptionSelf-efficacy scale (8 items), pre/post virtual lab-simulation training, N=189
ReferenceMakransky G, Thisgaard MW, Gadegaard H (2016). Virtual Simulations as Preparation for Lab Exercises: Assessing Learning of Key Laboratory Skills in Microbiology and Improvement of Essential Non-Cognitive Skills. PLOS ONE, 11(6), e0155895. https://doi.org/10.1371/journal.pone.0155895
DOI10.1371/journal.pone.0155895
LicenceCC BY 4.0
Source datahttps://doi.org/10.1371/journal.pone.0155895.s001

Size and shape

Responses2,808
Respondents189
Items8
Response categories5
Responses per respondent14.857
Responses per item351
Density1.857
LongitudinalTRUE

Classification

age rangeAdult (18+)
sampleEducational
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)dan

Item text

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

InstrumentMotivated Strategies for Learning Questionnaire (MSLQ), Self-Efficacy for Learning and Performance items, adapted to microbiology
Mean words per item13.250
Mean characters per item75.625
Mean characters per response14.800
Flesch-Kincaid grade level10.061

Columns

cov_agecov_groupcov_sexiditemrespwave

Get the data

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

Or load it directly in R or Python:

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("makransky_2016_self_efficacy")
# Python
pip install irw

import irw
df = irw.fetch("makransky_2016_self_efficacy")

Version and provenance

IRW versionv393
Redivis datasetitem_response_warehouse_3 v7.0
Redivis dataset DOI10.57761/pqqn-pm43
Manifest pin for this IRW versionv7.0
Metadata sourceirw_meta v23.0