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Artificial Intelligence and academic writing in higher education: a comparative analysis of linguistic indicators in student texts

G. D. da Silva I. Rhuan G. Tardo Ribeiro Junior Peres de Araujo M. Gilson Cardoso Chingulo Carolina Motter Pizoni-Escritório de Apoio Ao Editor Científico
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TL;DR

The results revealed relevant differences between the analyzed papers: texts produced in 2023 showed greater stylistic variation, the presence of authorial markers, and irregularities typical of human writing, whereas texts from 2025 presented a higher concentration of indicators associated with linguistic standardization, structural uniformity, and a reduction of individual markers of authorship.

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