Natural Language Processing and Computational Tools in Portuguese Language Teaching: Exploring Text Mining and Sentiment Analysis in the Development of Communicative Skills
Year: 2025
Type: article
Abstract: This research investigates the integration of digital technologies, specifically Natural Language Processing (NLP) and text mining, in Portuguese language teaching. In an increasingly digital educational scenario, these emerging tools offer new ways to personalize learning and improve reading and writing skills. The central issue involves the effectiveness of these technologies in improving students' communication skills, especially in challenging educational contexts. The main objective is to explore the impact of NLP and sentiment analysis on Portuguese language teaching, seeking innovations in the teaching-learning process. The research adopts the neoperspectivist paradigm gifedean , based on theories such as Piaget's Constructivism and Vygotsky 's Socio-Historical Psychology . The hypothetical-deductive method was used to test hypotheses about the effectiveness of technological tools in the educational context. The methodology included a Bibliographic and Documentary Narrative Review, with analysis of 50 articles and 20 books, extracted from databases such as Google Scholar, Scopus and Web of Science . The main findings revealed that the integration of NLP and text mining significantly contributes to the development of language skills, but some gaps, such as the limitation in the analysis of complex emotions, were identified. Limitations include the technological infrastructure in schools. The theoretical and methodological contributions offer a model for the use of these technologies in Portuguese language teaching. The added value lies in the innovation and in expanding the understanding of the applicability of these tools in modern teaching.
Authors: Breviário, Álaze Gabriel do, Souza, Jaine Marques de, Lucena, João Batista, Rago, Logan Faedda, Gomes, Marcelo D'Ávilla Teixeira, Fróes, Deusirene Sousa da Silva
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W6949615763
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