From Chatbots to Classrooms: Adaptive LLM Ecosystems Transforming Second Language Acquisition in the Post-COVID Era

https://doi.org/10.5281/zenodo.18029214

Abstract

The post-COVID era has witnessed a transformative agent in Second Language Acquisition(SLA).The integration of Artificial Intelligence (AI) into the language education and the reliance on adaptive Large Language Model (LLM) ecosystems are significantly reshaping the pedagogical practices. This study investigates how these GPT-powered conversational applications, networks and LLM-powered chat bots are transforming  classroom teaching techniques by providing  scalable support in meager-income situation , hybrid instructional platform and learner-specific flexibility. The study also highlights the recent developments and outcomes of  human-AI collaboration , customized  learning strategies  and SLA theories in language education, supported by LLM tools case study, language teacher interviews, and extensive literature review. Findings reflect that the integration of adaptive LLM ecosystems in SLA is ensuring  unprejudiced class environment , helping teachers to customize learner-focused instruction and reducing linguistic barriers. However, over-reliance, infrastructural inequality and ethical issues are possible challenges . The article emphasizes on a  purposeful and critically informed integration of these adaptive LLMs in Second Language pedagogy to promise more responsive, relatable and reliable outcomes of language education. Thus, shifting the conventional teaching approach toward hybrid, unbiased, student-centered and learner-specific ecosystems