Evidence map›Paper›PMID 42792445›Full record

ArticleBehavioral sciences (Basel, Switzerland)2026

Cultivating Technical Application Innovation in China's Vocational Undergraduate Education in the AI Era: A Symbolic Interaction Perspective.

Qiuchen Wu, Bin Bai

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.

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0citing papers in PubMed
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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

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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

2 authors.

Qiuchen WuCollege of Teacher Education, Ningbo University, Ningbo 315211, China.ORCID 0000-0002-3335-1689
Bin BaiFaculty of Education, Beijing Normal University, Beijing 100875, China.ORCID 0009-0002-0177-4393

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As artificial intelligence automates routine technical operations, the irreplaceable human contribution shifts toward technical application innovation-making useful improvements within existing technical frameworks through contextual judgment and adaptive problem-solving. China's vocational undergraduate education system, expanding from 15 pilot institutions in 2019 to 124 by June 2026, is uniquely positioned to cultivate this capability, yet how such innovation is activated through teacher-student interaction remains empirically unexamined. Grounded in symbolic interaction theory, this study employed an exploratory sequential mixed-methods design. A qualitative phase (n = 10) using theory-informed qualitative analysis produced a three-layer account of symbolic transmission, symbolic reception, and interactive mechanisms. A quantitative phase (N = 386) developed a 35-item scale and conducted an initial psychometric evaluation across six institutions. Structural equation modeling showed that interactive mechanisms had the strongest association with technical application innovation capability (β = 0.453), that symbolic reception showed stronger associations with the outcome than symbolic transmission in student self-reports, and that 38-44% of the association between symbolic rules and innovation passed through interactive mechanisms. These patterns are consistent with an innovation-as-emergence-from-interaction framework and provide a starting point for positioning vocational undergraduate education in the AI era.

Indexed as

artificial intelligencemixed methodssymbolic interaction theorytechnical application innovationvocational undergraduate education

Identifiers

PMID42792445
PMCPMC13603498

What OpenQuestion holds

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Registered trials

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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.