Generati e rigenerati: Uno studio preliminare sul trattamento di testi scientifici fra ChatGPT e abilità di studio
Authors
Alessandro PuglisiKey Information
Journal
Published in Vol. 2 No. 2 (2025) of AI-Linguistica. Linguistic Studies on AI-Generated Texts and Discourses.
AI-Linguistica. Linguistic Studies on AI-Generated Texts and Discourses is a new scholarly journal aiming at providing a publishing plateform for researchers from all areas of Linguistics (interfacing with neighboring fields: Communication Science, Media and Journalism Studies, Computational Linguistics) to reflect on generated texts from a variety of perspectives: theoretical, descriptive, and applied.
We understand ‘generated texts’ in a broad sense, including formats as diverse as texts generated by Large Language Models, AI-powered smart agents (i.e. chatbots, voice assistants, social bots etc.), writing assistance tools, template-based software, and neural machine translation services.
About the JournalAbstract
L’interazione tra uomo e macchina è entrata in una nuova fase dallo sviluppo dei Large Language Models, dal 2020 con GPT-3 e poi, soprattutto, dalla fine del 2022 con il rilascio dell’interfaccia conversazionale ChatGPT. Questi modelli hanno progressivamente acquisito un ruolo sempre più pervasivo in numerosi campi. Nel campo educativo le possibilità offerte dall’utilizzo di questi strumenti sono numerose, sebbene non manchino potenziali criticità. Il contributo si propone di esaminare il comportamento di ChatGPT 4o mini nell’esecuzione di tre tipi di task, legati alle abilità di studio, su testi scritti: riassunto, individuazione di punti chiave e semplificazione. I testi generati vengono successivamente analizzati dal punto di vista lessicale e sintattico, anche attraverso gli indici di leggibilità READ-IT. Tre tipologie di attività didattiche vengono dunque suggerite allo scopo di integrare l’intelligenza artificiale generativa nello sviluppo e mantenimento delle abilità di studio in ambito universitario.
The interaction between humans and machines has entered a new phase since the emergence of Large Language Models, starting with GPT-3 in 2020 and, more notably, with the release of the conversational interface ChatGPT at the end of 2022. These models have progressively taken on an increasingly pervasive role across numerous fields. In the educational domain, the possibilities offered using such tools are substantial, although potential challenges are not absent. This study aims to examine the behavior of ChatGPT 4o mini in performing three types of tasks related to study skills on written texts: summarization, key point identification, and simplification. The texts generated are subsequently analyzed from lexical and syntactic perspectives, including through the application of the READ-IT readability indices. Finally, three types of educational activities are proposed to integrate generative artificial intelligence into the development and maintenance of study skills in the university context.
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