4,200 responses from 350 respondents to 12 items.
One of 5 tables from the same source; this one is the learning table. The others are listed under Related tables.
| Description | Learning scale from Positive Education Tertiary course evaluation; N=350, 12 items, 1-4 Likert |
|---|---|
| Reference | Yang et al. (2021). Positive education in the tertiary setting: a case study evaluation of a compulsory year one course to develop [Dataset]. Figshare. DOI: 10.6084/m9.figshare.14870235.v1 |
| Licence | CC0 1.0 |
| Source data | https://figshare.com/articles/dataset/14870235 |
| Responses | 4,200 |
|---|---|
| Respondents | 350 |
| Items | 12 |
| Response categories | 4 |
| Responses per respondent | 12 |
| Responses per item | 350 |
| Density | 1 |
| Longitudinal | FALSE |
| sample | Educational |
|---|---|
| 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 | Life skills scale (bespoke EmPOWER positive education learning-outcome statements; Gan et al., 2022) |
|---|---|
| Mean words per item | 14.250 |
| Mean characters per item | 80.583 |
| Mean characters per response | 8.750 |
| Flesch-Kincaid grade level | 9.841 |
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, kern_2021_positive_edu.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.
| Column | What it is | Source column |
|---|---|---|
| IRW standard columns | ||
id | IRW standard Identifier for the focal unit being measured — typically a person, but sometimes another entity (e.g., a word in a lexical task). | made in the build script |
item | IRW standard Item identifier. | made in the build script |
resp | IRW standard Response value. | made in the build script |
What item codes and covariate values stand for is in the codebook released with the source data.
Or load it directly in R or Python:
# R (no account needed)
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("kern_2021_learning")
# Python (needs a free Redivis account)
pip install irw
import irw
df = irw.fetch("kern_2021_learning")
@misc{https://doi.org/10.6084/m9.figshare.14870235.v1,
doi = {10.6084/M9.FIGSHARE.14870235.V1},
url = {https://figshare.com/articles/dataset/Positive_education_in_the_tertiary_setting_a_case_study_evaluation_of_a_compulsory_year_one_course_to_develop_sense_of_purpose_leadership_self-management_emotional_intelligence_thinking_skills_and_positive_emotions/14870235/1},
author = {Yang, Gan Tzyy and Beevi, Zuhrah and Low, Jasmine and Lee, J.Peter and Hall, Deborah A.},
keywords = {170199 Psychology not elsewhere classified, FOS: Psychology},
title = {Positive education in the tertiary setting: a case study evaluation of a compulsory year one course to develop sense of purpose, leadership, self-management, emotional intelligence, thinking skills and positive emotions},
publisher = {figshare},
year = {2021},
copyright = {Creative Commons Zero v1.0 Universal}
}
| IRW version | v540 |
|---|---|
| Redivis dataset | item_response_warehouse_2 v33.0 |
| Redivis dataset DOI | 10.57761/6m04-m698 |
| Manifest pin for this IRW version | v33.0 |
| Metadata source | irw_meta v37.0 |