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TRUVACE RECORD VERSION
record: TRV-2026-2831
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T17:32:32.676069Z
status: published
lens: g_space
sector: education
headline: Exploring the impact of artificial intelligence on English language teaching: A meta-analysis
dek: The proposed meta-analysis study examines the pedagogical role of artificial intelligence (AI)-based interventions in English as a Foreign Language (EFL) education through a synthesis of empirical evidence of 23 peer-reviewed experimental and quasi-experimental experiments published in 2019–2025. Scheduling a strict systematic review process in accordance with the PRISMA principles, the work investigates AI solutions, including chatbots, automated writing assessment platforms and virtual reality applications, as…
gain_title: A meta-analysis of 23 experimental and quasi-experimental studies from 2019–2025 found AI tools were linked to a large pooled improvement in English-as-a-foreign-language learning outcomes (g = 1.10, 95% CI 0.75 to 1.44).
problem_title: (none)
trace_subject: (none)
gain_reading: A meta-analysis of 23 experimental and quasi-experimental studies from 2019–2025 found AI tools were linked to a large pooled improvement in English-as-a-foreign-language learning outcomes (g = 1.10, 95% CI 0.75 to 1.44).
gain_evidence: The combined findings reported a statistically significant and large overall effect (g = 1.10, SE = 0.18, 95 % CI [0.75, 1.44])
problem_reading: (none)
problem_evidence: (none)
quick_read: A meta-analysis pooled 23 peer-reviewed experimental and quasi-experimental studies published between 2019 and 2025 on AI in English as a Foreign Language teaching. It found a large overall effect on learning outcomes (Hedges' g = 1.10, 95% CI 0.75 to 1.44).

The gains showed up in writing accuracy, speaking fluency and learner motivation, along with lower anxiety and greater enjoyment. Measures of motivation and engagement rose more than countable measures such as word count.

Results varied widely between studies (I2 = 92.66%), so the average effect hides large differences in tools, learners and measurement methods.
limitation: Heterogeneity across the 23 studies was very high (I2 = 92.66%), so results differ substantially by tool, learner group and measurement method.
tag: Evidence-backed gain
key_points: The review followed PRISMA procedures and covered 23 peer-reviewed experimental and quasi-experimental studies from 2019 to 2025. | The AI tools studied included chatbots, automated writing assessment platforms and virtual reality applications. | Effect sizes were calculated as Hedges' g in a random-effects model using Comprehensive Meta-Analysis software. | The pooled effect was g = 1.10 (SE = 0.18, 95% CI 0.75 to 1.44). | Affective measures such as motivation and engagement showed stronger increases than purely quantitative measures such as word count. | Heterogeneity was high (I2 = 92.66%), pointing to contextual and methodological differences. | The authors recommend combining AI with teacher input for ethical, learner-centred teaching.
rundown: The authors searched for experimental and quasi-experimental studies on AI in English as a Foreign Language classrooms and screened them using PRISMA principles, ending with 23 studies from 2019 to 2025. The interventions included chatbots, automated writing assessment platforms and virtual reality applications.

Pooling the studies in a random-effects model gave a large overall effect of g = 1.10 with a confidence interval of 0.75 to 1.44. The improvements covered writing accuracy, speaking fluency and learner motivation, and learners also reported less anxiety and more enjoyment.

A subgroup analysis found that the type of measurement tool moderated the effect: affective variables such as motivation and engagement rose more than quantitative ones such as word count. The authors recommend teachers and AI working together.
sources:
- peer_reviewed | Acta Psychologica | https://doi.org/10.1016/j.actpsy.2025.105649 | 2025-10-01
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