Artificial intelligence (AI)-Based English Learning Innovation to Improve Literacy Abilities

Abstract

Artificial Intelligence (AI) has rapidly transformed English Language Teaching (ELT), altering how reading, writing, and oral skills are developed. However, educational institutions often struggle to synthesize isolated AI tools into cohesive, structured curricula, while ignoring the crucial dimension of AI literacy. This study conducts a systematic research synthesis and comparative meta-analysis of recent empirical interventions and conceptual frameworks (spanning 2024–2026) to evaluate the impact of AI-based innovations on English literacy. By analyzing quantitative and qualitative outcomes across multi-dimensional literacy domains—specifically reading comprehension, oral reading fluency, and academic writing—we assess how AI interventions affect cognitive, behavioral, and meta-cognitive performance. The results demonstrate that targeted AI tools, such as Microsoft Teams' Reading Progress and conversational chatbots, yield statistically significant improvements in oral reading fluency (  ) and reading comprehension. Moreover, AI integration fosters self-regulated learning behaviors (including goal-setting and self-reflection) and enhances student engagement (attentiveness, motivation). However, challenges regarding student over-reliance, lack of structured curricula, and algorithmic biases persist. This paper proposes an integrated pedagogical model that couples functional language acquisition with structured AI literacy practices (understanding, evaluating, and using AI) to foster critical, ethical, and self-regulated English learners