Evidence map›Paper›PMID 42865744›Full record

ArticleFrontiers in psychology2026

Perceived generative AI teaching intelligence and pre-service teachers' professional identity: double-edged pathways through professional agency and AI replacement threat.

Haoyu Zhao

Abstract read
In one paragraph

Article in Frontiers in psychology, 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

1 author.

Haoyu ZhaoHubei Communications Research Institute, Hubei Communications Technical College, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Generative artificial intelligence (GenAI) is increasingly used in teacher education for lesson planning, feedback, and assessment support. However, how perceived GenAI teaching intelligence relates to pre-service teachers' professional identity remains unclear. This study examined a double-edged model linking perceived intelligence to professional identity through professional agency and AI replacement threat, with teacher-AI complementarity beliefs moderating these pathways. In a task-based between-subjects experiment, 598 pre-service teachers were randomly assigned to high- or low-intelligence GenAI teaching-support conditions. Complementarity beliefs and baseline professional identity were measured before exposure; perceived intelligence, professional agency, replacement threat, and post-task identity were assessed afterward. Confirmatory factor analysis and conditional process analyses with 5,000 bootstrap resamples tested the model. Participants in the high-intelligence condition reported greater agency and replacement threat, but no statistically significant between-condition difference in post-task identity was detected. Perceived intelligence was positively associated with both agency and replacement threat, which were, respectively, positively and negatively associated with professional identity. Stronger complementarity beliefs were associated with a stronger agency pathway and a weaker replacement-threat pathway. These findings are consistent with two opposing identity-relevant processes following exposure to capable GenAI. Teacher education should support professional judgment and clarify human-AI role boundaries when integrating GenAI into teaching practice.

Indexed as

AI replacement threatgenerative artificial intelligenceperceived intelligencepre-service teachersteacher–AI complementarity beliefsteacher educationteacher professional agencyteacher professional identity

Identifiers

PMID42865744
PMCPMC13655131

What Socratic holds

Textmetadata
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 Socratic graph.