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Introduction The way we understand language—how it is acquired, processed, and produced—has shifted considerably over the past few decades. In language teaching, Michael Lewis’s Lexical Approach challenged traditional grammar-first models by emphasizing the importance of word combinations, or collocations , in language use. In the field of artificial intelligence, large language models (LLMs) like GPT-4 or Claude have also abandoned rule-based systems in favor of pattern recognition. Though born in different disciplines, both approaches rest on a similar foundation: that fluency and meaning emerge not from abstract rules, but from repeated exposure to patterned language. This article explores the surprising alignment between Lewis’s pedagogical model and the operational logic of LLMs. By examining the underlying principles of the Lexical Approach, and mapping them onto the behavior of AI text generators, we can better understand not only how machines learn to write, but also how h...

Introduction: The exploration of language acquisition has given rise to a variety of theoretical perspectives, each shedding light on how humans acquire , store , organize , and retrieve lexical items . Yet, these perspectives often employ problematic terminology rooted in deep metaphysical assumptions, portraying the mind as a container where linguistic units are neatly stored and accessed at will. This "container metaphor" closely aligns with the nomenclaturist perspective of language, which prioritizes the identification and categorization of individual lexical units. However, Ferdinand de Saussure's linguistic approach challenges this view, advocating for a systemic comprehension of language. According to Saussure, identity arises from within the linguistic system itself, blurring the traditional boundaries between phonetics, grammar and vocabulary. Inside the Mind: Insights from Behaviorism, Cognitive Psychology, and Connectionist Theories on Langua...