AI-Driven Vocabulary Development in ESL Context: Advancing Autonomous Learning Through Technology

Abstract

For ESL learners, the vocabulary learning process becomes a laboriously daunting one due to insufficient social and educational input. According to Schneider et al. (2002), the process of second language learning, specifically the vocabulary of the target language, requires the “ability to produce, differentiate, connect, and be bidirectional” (p. 419). In this situation, technology seems to be the ultimate savior. Technology is changing the pedagogical possibilities at a phenomenal rate, and the effects of this change have reached beyond the classrooms. With the advent of Artificial intelligence i.e. AI, technology has become more powerful, accessible, portable and adaptable providing learners with tools to make their learning personalized and accelerated. A shift has also occurred in the pedagogical perspectives and practices as well, bringing learners to the forefront instead of teachers. In such a scenario, TALL (Technology Assisted Language Learning) is expected to play a significant role in the teaching and learning of a second or a foreign language. Keeping in perspective Beatty’s (2010) assertion about finding ways to create “a better fit between good pedagogy and technology” (p. 206), this paper explores the potential of technology-assisted, autonomous, and self-regulated learning approaches and practices for lexical enrichment in ESL contexts. It investigates how AI-driven tools and applications can bridge the gap between theoretical and pedagogical frameworks and practical implementation, enhancing vocabulary acquisition and learner autonomy beyond the traditional classroom environment.