Evidence map›Paper›PMID 40294036›Full record

ArticlePloS one2025

University students' self-assessment of data literacy: A validation study.

Jeonghyun Kim, Lingzi Hong, Ayoung Yoon

Abstract readValidation Study
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jeonghyun KimDepartment of Information Science, University of North Texas, Denton, TX, United States of America.ORCID 0000-0002-2514-2342
Lingzi HongAnuradha and Vikas Sinha Department of Data Science, University of North Texas, Denton, TX, United States of America.
Ayoung YoonDepartment of Library and Information Science, Indiana University Indianapolis (IUI), Indianapolis, IN, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As data literacy has emerged as a critical skill for professionals across industries, educators in higher education have incorporated it into their curricula and instruction. Understanding and evaluating the factors that shape an individual's data literacy is important for benchmarking proficiency and tailoring curricula, yet the underlying components and structure of data literacy for students in four-year institutions are unknown. This study validated the Data Literacy Self-Efficacy Scale (DLSES) with 1,816 students enrolled in two four-year institutions. Exploratory and confirmatory factor analyses were conducted to determine the construct of the scale, and the item analysis was used to address the validity of the items on the scale. The exploratory factor analysis identified eight distinct factors comprising 29 items. The results of confirmatory factor analysis showed a good model fit, CFI = 0.994, TLI = 0.994, RMSEA = 0.053, SRMR = 0.044. This study demonstrated the 29-item refined version of the DLSES to be a reliable and valid tool for measuring individuals' self-efficacy levels for data literacy. Furthermore, the scale could form the basis for curriculum development and help educators design targeted interventions that address specific learning needs.

Indexed as

Information LiteracySelf-AssessmentStudentsAdolescentAdultFactor Analysis, StatisticalFemaleHumansMaleSelf EfficacySurveys and QuestionnairesUniversitiesYoung Adult

Identifiers

PMID40294036
PMCPMC12036854

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.