Computational Modeling of Second Language Learning

Abstract Computational modeling has played a significant role in advancing language studies. Over the past three decades, this approach has also been successfully applied to the study of second language learning and bilingualism, and several computational bilingual models have been developed, mostly within the framework of connectionism. In this entry, we offer an overview of these models, introducing their underlying connectionist mechanisms, highlighting their main contributions, and discussing their limitations. Given the increasing popularity of large language models (LLMs) such as ChatGPT, we also examine the opportunities and challenges associated with using LLMs for studying second language learning.