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TRUVACE RECORD VERSION
record: TRV-2026-2463
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-11T01:46:52.406970Z
status: published
lens: p_space
sector: labor
headline: Artificial intelligence (AI) adoption and Chinese art teachers' career exploration behavior: The roles of job substitution risks, job insecurity, and organizational AI readiness
dek: The increasing use of artificial intelligence (AI) in art education raises questions about teachers' professional security and career development. Drawing primarily on Conservation of Resources (COR) theory and, in a complementary manner, on Career Construction Theory (CCT), this cross-sectional study examined associations among AI adoption, perceived job substitution risk, job insecurity, career exploration behavior, and organizational AI readiness. Survey data from 381 Chinese art teachers were analyzed using…
gain_title: (none)
problem_title: In a survey of 381 Chinese art teachers, heavier AI use was associated with greater perceived risk of being replaced (B = .40) and greater job insecurity (B = .37).
trace_subject: (none)
gain_reading: (none)
gain_evidence: (none)
problem_reading: In a survey of 381 Chinese art teachers, heavier AI use was associated with greater perceived risk of being replaced (B = .40) and greater job insecurity (B = .37).
problem_evidence: AI adoption was positively associated with job substitution risk (B = .40, SE = .07, p < .001) and job insecurity (B = .37, SE = .08, p < .001).
quick_read: A cross-sectional survey of 381 art teachers at Chinese universities found that teachers who used AI tools more also reported more fear that AI could replace their work and more worry about their jobs. They also reported more career exploration over the previous three months.

The association between AI use and career exploration was strongest where teachers rated their institution as more ready for AI: negligible at low readiness (B = -.02), moderate at average readiness (B = .27) and larger at high readiness (B = .57).

The data cannot show cause and effect. Teachers already exploring other careers may be more inclined to adopt AI, and the survey did not measure why teachers explored, whether from threat or interest in growth.
limitation: The cross-sectional, self-reported design cannot establish causal order, and reverse causality is possible. Recruitment through social contacts may have favored technologically engaged teachers, and exploration motives were not measured.
tag: Evidence-backed problem
key_points: Of 500 questionnaires distributed online between July 17 and September 26, 2025, 439 came back and 381 were valid after screening. | AI adoption was linked to job substitution risk (B = .40) and job insecurity (B = .37); substitution risk was in turn linked to job insecurity (B = .22). | The total association between AI adoption and career exploration was B = .51; it fell to B = .27 once substitution risk and insecurity were accounted for. | Substitution risk accounted for an indirect association of B = .14 and job insecurity for B = .08; the combined path was small (B = .02). | The interaction between AI adoption and organizational AI readiness was positive (B = .36, p < .001). | The study controlled for gender, age, education, teaching experience, institutional level and weekly AI use, but not professional rank or prior digital skills.
rundown: Teachers rated AI adoption, substitution risk, job insecurity, organizational AI readiness and career exploration on 7-point scales across 22 items. Participants were recruited through personal contacts at selected universities, and respondents received a small gift worth 10 RMB. Data were analysed with a latent-variable structural equation model in Mplus 7.4.

Exploration was linked to substitution risk (B = .35) and job insecurity (B = .22). The authors interpret this through Conservation of Resources theory, with Career Construction Theory suggesting that exploration may reflect threat, growth or both.

The authors recommend that schools communicate AI's supportive role, invest in infrastructure and arts-specific training, and that policymakers add AI literacy to art teacher preparation. The paper was in revision at PLOS One, with the editor asking for changes on method bias and causal wording.
sources:
- peer_reviewed | PLOS One | https://doi.org/10.1371/journal.pone.0362478 | 2026-11-06
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