Reconceptualizing Grammatical Complexity in Contemporary English Discourse

Retno Dwigustini; Muji Endah Palupi; Fitri Apriyanti

doi:10.55606/jupensi.v6i2.7508

Authors

Retno Dwigustini Universitas BSI
Muji Endah Palupi Universitas BSI
Fitri Apriyanti Universitas BSI

DOI:

https://doi.org/10.55606/jupensi.v6i2.7508

Keywords:

Academic Discourse, Corpus Linguistics, Digital Discourse, English As A Lingua Franca, Grammatical Complexity

Abstract

Grammatical complexity is a key concept in linguistics, second language acquisition, discourse analysis, and academic writing assessment. Traditionally, it has been measured through structural indicators such as sentence length, clause number, and syntactic density. However, contemporary English discourse demonstrates that grammatical complexity extends beyond formal syntactic measures, as English is increasingly used across academic, professional, digital, and AI-mediated contexts. This article aims to reconceptualize grammatical complexity through a qualitative-conceptual approach based on literature review and thematic analysis. The reviewed literature includes syntactic complexity, corpus linguistics, systemic functional linguistics, academic discourse, English as a Lingua Franca, digital discourse, and AI-assisted texts. The findings indicate that grammatical complexity should be viewed as a multidimensional construct comprising four dimensions: structural, informational, functional, and discursive complexity. These dimensions explain how grammatical choices contribute to idea organization, communicative purposes, rhetorical effectiveness, and contextual appropriateness across genres and media. The study expands the concept of grammatical complexity from a structural proficiency indicator to a contextual meaning-making resource. It also highlights methodological implications by encouraging the integration of corpus, discourse, genre, and functional linguistic approaches, with practical relevance for English language teaching, academic writing assessment, digital literacy, and AI-generated text evaluation.

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