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TRUVACE RECORD VERSION
record: TRV-2026-2824
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T17:30:25.326441Z
status: published
lens: g_space
sector: education
headline: Estimating the Effect of ChatGPT-Assisted Instruction on Learning Outcomes in TVET, Vocational Education, and Engineering Education: A Meta-Analysis
dek: Aim/Purpose: The aim of this study is to synthesize empirical evidence from Scopus-indexed studies and estimate the pooled effect of ChatGPT-assisted instruction on learning outcomes across the included TVET, vocational education, and engineering education contexts. Background: The rapid proliferation of ChatGPT has attracted growing interest in its potential to facilitate learning in TVET, vocational education, and engineering education. However, empirical findings remain inconsistent. Some studies report large…
gain_title: A meta-analysis of 10 experimental and quasi-experimental studies in vocational, engineering and related courses found ChatGPT-assisted instruction beat comparison teaching, with a moderate pooled effect (Hedges' g = 0.739, 95% CI 0.469–1.010).
problem_title: (none)
trace_subject: (none)
gain_reading: A meta-analysis of 10 experimental and quasi-experimental studies in vocational, engineering and related courses found ChatGPT-assisted instruction beat comparison teaching, with a moderate pooled effect (Hedges' g = 0.739, 95% CI 0.469–1.010).
gain_evidence: ChatGPT-assisted instruction showed a statistically significant, moderate positive pooled effect | Hedges’ g = 0.739, 95% CI = 0.469–1.010, p < .001
problem_reading: (none)
problem_evidence: (none)
quick_read: A meta-analysis by researchers at Universitas Negeri Padang pooled 10 experimental or quasi-experimental studies from Scopus published 2022–2026. It found that students taught with ChatGPT scored higher than comparison groups on cognitive, affective and psychomotor outcomes, with a pooled Hedges' g of 0.739 (95% CI 0.469–1.010), a moderate effect.

Results varied widely between studies (I² = 83.12%), from g = 0.12 for creative ideation among 51 students in a crossover trial to 1.54 for conceptual understanding in a thermodynamics course of 120 students. Restricting the analysis to directly assessed cognitive, skill and performance outcomes gave 0.689, still significant.

The evidence comes mostly from higher-education programming and engineering courses. Hands-on trade programs, apprenticeships and non-higher-education vocational learners were poorly represented or absent, so the authors say the estimate should not be generalised to all vocational or engineering settings.
limitation: The review covered only English-language, open-access Scopus studies from 2022 to 2026, so it may have missed studies and the pooled estimate may be higher or lower than the full literature would give.
tag: Evidence-backed gain
key_points: Ten studies were pooled: 4 assessed as randomized trials and 6 as quasi-experiments, with group sizes from 21 to 150 students. | The pooled effect was g = 0.739 (SE 0.138, z = 5.362, p < .001) using a random-effects model. | Heterogeneity was substantial (Q(9) = 49.838, τ² = 0.153, I² = 83.121%), so the figure is an average, not uniform effectiveness. | Results held across assumed within-study correlations: pooled g ranged from 0.730 to 0.753. | Of 22 reported outcomes, 13 (59.1%) were cognitive, 8 (36.4%) affective and 1 (4.5%) psychomotor. | Rosenthal's fail-safe N was 557 and Kendall's τ = 0.250 (p = 0.321) found no clear funnel-plot asymmetry, but with 10 studies these tests had limited power. | Concerns in the primary studies included inaccurate or biased outputs, plagiarism, over-reliance, reduced creativity, privacy and subscription costs.
rundown: The authors searched Scopus on April 8, 2026 for ChatGPT studies in TVET, vocational and engineering education, then screened for original experimental or quasi-experimental, English-language, open-access studies. Ten had enough statistics to calculate effect sizes. One author did all screening, and quality was appraised with JBI checklists.

Study-level effects ranged widely. A programming experiment with 45 students gave a composite g of 1.07, a 61-student peer-assessment trial gave 0.99, a cluster-randomized trial of 254 students gave 0.45, and a tourism statistics study of 300 students gave 0.64 for creative thinking. The crossover study of 51 participants gave 0.12.

The included papers named opportunities such as programming support and personalised learning, alongside concerns about over-reliance and accuracy. Proposed strategies, including prompt training and verifying AI answers, were not tested as moderators, so the authors treat them as proposals. They recommend cautious use of ChatGPT as a supplementary tool.
sources:
- peer_reviewed | Journal of Information Technology Education: Research | https://doi.org/10.28945/5877 | 2026-01-01
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