From Collocations to Computation: The Lexical Approach and LLMs
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...