Evidence map›Paper›PMID 42510287›Full record

ArticleBehavioral sciences (Basel, Switzerland)2026

Research on the Impact of Generative Artificial Intelligence Usage Behavior on the Learning Outcomes of Higher Vocational Students.

Yafeng Song, Kangjian Zhao, Li Li, Wei Dong

Abstract read
In one paragraph

Article in Behavioral sciences (Basel, Switzerland), 2026. 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

4 authors.

Yafeng SongSchool of Education, Tianjin University, Tianjin 300350, China.ORCID 0009-0005-8134-2006
Kangjian ZhaoSchool of Education, Tianjin University, Tianjin 300350, China.ORCID 0009-0004-2494-4556
Li LiSchool of Education, Tianjin University, Tianjin 300350, China.
Wei DongSchool of Education, Tianjin University, Tianjin 300350, China.

Funding

Chinese Academy of Social Sciences BJA250170
6 · The paper itself

Abstract

Generative Artificial Intelligence (GenAI) has been increasingly integrated into vocational education teaching and students' learning. Thus, instructing higher vocational students to use GenAI effectively and improving their self-reported perceptions of learning outcomes are critical. Based on the talent development requirements of vocational education, this study developed and validated the GenAI Usage Behavior Scale and the Higher Vocational Students' Perceived Learning Outcomes Scale. Subsequently, an empirical analysis was conducted using data from 1110 valid questionnaires collected from Chinese higher vocational students. According to the descriptive statistical analysis, the overall usage behavior of higher vocational students was generally at a medium-high level. They performed relatively well in terms of usage habits, moderately in usage contexts, and showed a relatively low frequency of use. The overall evaluation for higher vocational students' perceived learning outcomes was rated as above average with competency development ranking highest, followed by skill application and knowledge mastery. As for group differences, the results of the independent samples

Indexed as

generative artificial intelligencehigher vocational studentsimpactperceived learning outcomesusage behavior

Identifiers

PMID42510287
PMCPMC13405536

What OpenQuestion holds

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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.