merlo2025_eng_emotional

9,585 responses from 1,065 respondents to 9 items.

About this table

DescriptionStudent Engagement — Emotional subscale (9 items); Italian university students; N=1065; 1-7 Likert
ReferenceMerlo, G., Jaforte, L., Vassallo, M., & Pozzetti, I. (2025). Dataset for: Sleep Quality as a Mediator Between Lifestyle and Cognitive and Agentic Student Engagement [Dataset]. figshare. https://doi.org/10.6084/m9.figshare.30195541.v1
LicenceCC BY 4.0
Source datahttps://figshare.com/articles/dataset/Dataset_for_Sleep_Quality_as_a_Mediator_Between_Lifestyle_and_Cognitive_and_Agentic_Student_Engagement_A_Structural_Equation_Modeling_Approach/30195541

Size and shape

Responses9,585
Respondents1,065
Items9
Response categories7
Responses per respondent9
Responses per item1,065
Density1
LongitudinalFALSE

Classification

age rangeMixed
child age (for child-focused studies)Adolescent (12-18y)
sampleEducational
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)ita

Item text

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

InstrumentStudent Engagement Scale (SES; Mameli & Passini, 2017) - affective (emotional) engagement subscale
Mean words per item7.333
Mean characters per item34.778
Mean characters per response6
Flesch-Kincaid grade level3.003

Columns

cov_agecov_heightcov_sexcov_weightiditemresp

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("merlo2025_eng_emotional")
# Python
pip install irw

import irw
df = irw.fetch("merlo2025_eng_emotional")

Version and provenance

IRW versionv393
Redivis datasetitem_response_warehouse_2 v19.0
Redivis dataset DOI10.57761/qtx5-4m80
Manifest pin for this IRW versionv19.0
Metadata sourceirw_meta v23.0