A Systematic Review of Emerging Technology Applications for Teaching English as a Foreign Language Across Different Educational Levels

Synthesis: In brief: Liu, Hashim, and Sulaiman systematically review and meta-analyze 33 experimental and quasi-experimental studies (N = 3,181) on emerging technologies for teaching English as a foreign language (TEFL) across primary, secondary, and tertiary education. They find a small-to-moderate positive overall effect (Hedges' g = 0.38, 95% CI [0.26, 0.50]) with substantial heterogeneity; effect sizes rose with educational level (primary g = 0.29, secondary g = 0.35, tertiary g = 0.44) and were largest for VR/AR, with productive skills (speaking, writing) showing greater gains than receptive skills.

This systematic review and meta-analysis examines the applications, effectiveness, and challenges of emerging technologies for TEFL. The technologies investigated span mobile-assisted language learning apps, AI-powered tools (chatbots, automated writing evaluation, intelligent tutoring systems), virtual and augmented reality environments, gamification platforms, and social media tools. Following PRISMA 2020 guidelines, 33 studies (N = 3,181) from Web of Science, Scopus, and ERIC (2015–2024) were analyzed with a random-effects meta-analysis.

The overall effect is small-to-moderate (g = 0.38) with substantial heterogeneity (I² = 90.14%). Subgroup analyses show effect sizes increasing with educational level — primary (g = 0.29), secondary (g = 0.35), tertiary (g = 0.44) — and VR/AR yielding the largest effects among technology types. Across skill domains, productive skills (speaking and writing) showed greater gains than receptive skills (reading and listening), while vocabulary and grammar also improved significantly. The larger tertiary-level effects likely reflect greater learner autonomy and more sophisticated technological infrastructure. Trim-and-fill adjustment for publication bias was applied.

Key Findings

• 33 experimental/quasi-experimental studies (N = 3,181), 2015–2024, across primary, secondary, and tertiary education.
• Small-to-moderate overall effect: Hedges' g = 0.38, 95% CI [0.26, 0.50], p < 0.001, with substantial heterogeneity (I² = 90.14%).
• Effect sizes rose with educational level: primary g = 0.29, secondary g = 0.35, tertiary g = 0.44.
• VR/AR yielded the largest effects among technology types.
• Productive skills (speaking, writing) showed greater gains than receptive skills (reading, listening); vocabulary and grammar also improved significantly.
• Tertiary effects likely reflect greater learner autonomy and more sophisticated technological infrastructure.

Connected Concepts

• Language Learning — the learning domain
• English Education (EAP / EFL / ESL) — the EFL context
• Generative AI — AI-powered chatbots and automated writing evaluation
• Intelligent Tutoring — one of the AI tool categories
• K-12 — primary and secondary settings
• Higher Education — tertiary settings
• Game-Based Learning — gamification platforms

Connected Articles

• Acceptance of AI-Assisted English Language Learning Tools in Higher Education: Psychological Correlates Across Disciplinary and Proficiency Groups — acceptance of AI tools for English
• Students' experiences of using ChatGPT for English language learning: a qualitative study in a Malaysian higher education institution — ChatGPT in English language learning
• AI tools in Arab University English classrooms: Looking back and forward — AI tools in Arabic English classrooms
• AI-Generated versus Human-Developed Assessment Tasks in EFL Context: Insights from TPCK Model — AI vs human assessment in EFL

Citation

Liu, M., Hashim, H., & Sulaiman, N. A. (2026). A systematic review of emerging technology applications for teaching English as a foreign language across different educational levels. Educational Research Review, 52, 100795.