Artificial Intelligence in Supporting Self-Regulated Reading among English as a Second Language Learners: A Systematic Review
TL;DR
Artificial intelligence applications, particularly adaptive learning platforms and conversational agents, effectively support reading development by giving feedback, personal learning experiences, and opportunities for learners to monitor their own progress.
Abstract
Artificial intelligence (AI) has become increasingly prominent in English language education, offering new possibilities for supporting reading instruction and independent learning among English as a second language (ESL) learner. This study aims to examine the existing body of empirical research concerning the use of AI to improve reading skills and encourage self-regulated learning (SRL). The significance of this study lies in its synthesis of fragmented data to provide a unified framework for future technology-mediated reading instruction. Using a systematic literature review approach that strictly followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, 19 empirical studies were extracted from major academic databases including Scopus, ERIC, and Google Scholar and analyzed through thematic analysis. The synthesized results reveal that AI applications, particularly adaptive learning platforms and conversational agents, effectively support reading development by giving feedback, personal learning experiences, and opportunities for learners to monitor their own progress. Concurrently, the results highlight several concerns, including excessive dependence on technological support and limited development of higher-order reading skills. Overall, AI can make a valuable contribution to reading instruction when integrated with pedagogical practices that encourage learner independence. Future research should investigate the influence of AI on reading comprehension through longitudinal studies conducted in authentic educational settings.
