The cognitive-affective impact of generative AI on EFL/ESL learning: A meta-analysis

Abstract

Since ChatGPT’s public release in November 2022, generative artificial intelligence (GenAI) has rapidly transformed English as a Foreign/Second Language (EFL/ESL) education, yet its precise impact on learning outcomes remains subject to debate. This systematic review and meta-analysis synthesizes evidence from 33 pooled empirical studies and 6 narrative-synthesis studies examining GenAI’s effects on language learning outcomes from November 2022 to March 2026. Following PRISMA 2020 guidelines, we searched multiple databases, applied a pre-specified effect-size verification rule to screen for reporting anomalies and calculated random-effects models for three outcome domains. Results revealed a large overall effect (Hedges’ g = 1.253, 95% CI [0.954, 1.542], I² = 94.4%). Language performance outcomes showed strong effects (g = 1.197) with substantial heterogeneity (I² = 88.4%). Affective outcomes demonstrated a large but highly heterogeneous effect (g = 1.3347, I² = 98.3%) while self-regulation outcomes yielded a large but non-significant preliminary estimate (g = 1.400, p = .187, I² = 99.1%). Research design and intervention duration emerged as significant moderators with experimental designs producing the strongest effects. The literature is overwhelmingly concentrated at the tertiary level (87.9%), and a tertiary-only sensitivity analysis confirmed that pooled estimates are not driven by aggregation across developmental stages. Egger’s test indicated no evidence of publication bias in the corrected dataset (p = .49). Evidence certainty was rated MODERATE using GRADE criteria. These findings support GenAI’s effectiveness in EFL/ESL learning while emphasizing the importance of implementation design, the context-sensitivity of affective outcomes, and the need for sustained metacognitive scaffolding to promote self-regulation.