Evidence map›Paper›PMID 41401177›Full record

ArticlePloS one2025

From training to practice: A multi-group analysis of factors influencing K-12 teachers'integration of Digital Educational Resources (DERs).

Qizhong Ou, Songqiao Wu, Yilu Jiang, Zhenni He, Haiqiu Luo

Abstract read
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. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Qizhong OuSchool of Artificial Intelligence, Nanning Normal University, Nanning, China.ORCID https://orcid.org/0000-0002-7839-9096
Songqiao WuSchool of Artificial Intelligence, Nanning Normal University, Nanning, China.
Yilu JiangSchool of Artificial Intelligence, Nanning Normal University, Nanning, China.
Zhenni HeSchool of Artificial Intelligence, Nanning Normal University, Nanning, China.
Haiqiu LuoSchool of Artificial Intelligence, Nanning Normal University, Nanning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ensuring teachers effectively integrate digital technologies is crucial for modernizing education, yet the success of large-scale training initiatives often varies. This study investigates the factors shaping technology adoption among 2,821 K-12 teachers following a national digital literacy program. Using a Structural Equation Model (SEM) based on the UTAUT framework, this research employs a multi-group analysis to examine how adoption drivers differ across key demographic segments. Results show that social influence and performance expectancy are the primary drivers of teachers' intention to use digital resources, which in turn strongly predicts actual use. Notably, the influence of these factors varies significantly depending on teachers' regional context, educational stage, and prior digital experience, highlighting the limitations of a uniform approach to professional development. The findings provide a nuanced evidence base for designing more targeted and effective teacher support strategies.

Indexed as

Digital TechnologySchool TeachersAdultFemaleHumansMaleMiddle Aged

Identifiers

PMID41401177
PMCPMC12707651

What OpenQuestion holds

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LicenceCC BY
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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.