Evidence map›Paper›PMID 42352755›Full record

ArticleBehavioral sciences (Basel, Switzerland)2026

From Foundation to Intelligence Integration: The Synergistic Associations of ICT and AI Support with Pre-Service Teachers' TPACK Development.

Xu Liu, Jiaoyang Du, Jiacheng Wang, Huan Song

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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0cells of the map it votes in
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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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.

Xu LiuCenter for Teacher Education Research, Faculty of Education, Beijing Normal University, Beijing 100875, China.ORCID 0009-0003-3380-3897
Jiaoyang DuCenter for Teacher Education Research, Faculty of Education, Beijing Normal University, Beijing 100875, China.ORCID 0009-0003-6975-7108
Jiacheng WangCenter for Teacher Education Research, Faculty of Education, Beijing Normal University, Beijing 100875, China.
Huan SongCenter for Teacher Education Research, Faculty of Education, Beijing Normal University, Beijing 100875, China.ORCID 0000-0001-6053-6972

Funding

2025 National Planning for Educational Science PhD Program FRA250472
6 · The paper itself

Abstract

Digital-intelligence transformation in education has made pre-service teachers' Technological Pedagogical Content Knowledge (TPACK) a strategic concern in teacher preparation. Survey data from 11,818 pre-service teachers across 17 local normal universities in China were analyzed through hierarchical regression, quantile regression, and structural equation modeling to examine how perceived university ICT support and perceived AI support in education are associated with self-reported TPACK. Both forms of support showed significant direct and model-conform indirect associations with self-reported TPACK, but the quantile coefficients varied across the TPACK distribution: university ICT support showed a modestly fluctuating descriptive pattern, whereas AI support in education peaked at the median and attenuated at upper quantiles. ICT self-efficacy and AI competency expectancy each formed significant indirect pathways in the hypothesized model, although the ICT pathway was more strongly indirect and the AI pathway remained more strongly direct. Additional checks of university-level ICCs, cluster-robust standard errors, and measurement invariance across key subgroups supported the robustness and comparability of the findings. These patterns clarify how perceived ICT and AI support are differentially associated with self-reported TPACK and provide empirical grounds for more precise, human-in-the-loop support designs in teacher education.

Indexed as

AI competency expectancyAI support in educationICT self-efficacypre-service teachersTPACKuniversity ICT support

Identifiers

PMID42352755
PMCPMC13295338

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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.