Artificial intelligence and personalized distance learning: paths to autonomy and efficiency in the 1:1 model

Authors

  • Paulo Henrique Leitão Lopes Junior Faculdade (Autor convidado) Author

Keywords:

artificial intelligence, personalized learning, distance learning

Abstract

This article discusses the applications of artificial intelligence (AI) in education, focusing on the 1:1 personalized distance learning model—an AI system dedicated to each student. The proposal integrates Brazilian educational policy guidelines, particularly the National Curricular Guidelines (DCNs), and analyzes how AI can be used to adapt teaching methodologies, content, and time management based on the individual characteristics of each student. The article presents the pedagogical potential of using techniques such as the Pomodoro method, integrated with AI, to promote autonomy, focus, and continuous student development in virtual learning environments.

Author Biography

  • Paulo Henrique Leitão Lopes Junior, Faculdade (Autor convidado)
    With a degree in Literature from the Federal University of Ceará (UFC), he teaches Portuguese, Literature, and Writing for high school students, with experience preparing for university entrance exams such as ENEM (National High School Exam), FUVEST (National High School Exam), and other public service exams. He also works with translation, academic writing, and proofreading, developing content with linguistic rigor and argumentative excellence.

References

BRASIL. Ministério da Educação. Diretrizes Curriculares Nacionais para a Educação Básica. Brasília: MEC, 2013.

BRASIL. Ministério da Educação. Base Nacional Comum Curricular (BNCC). Brasília: MEC, 2017.

LUCKIN, R.; HOLMES, W.; GRIFFITHS, M.; FORCIER, L. B. Intelligence unleashed: An argument for AI in education. London: Pearson, 2016.

ROSE, D. H.; DALTON, B. Learning to read in the digital age. Mind, Brain, and Education, [S.l.], v. 3, n. 2, p. 74–83, 2009. DOI: https://doi.org/10.1111/j.1751-228X.2009.01057.x. Acesso em: 16 maio 2025.

SCHUNK, D. H. Teorias de aprendizagem: uma perspectiva educacional. 6. ed. Porto Alegre: Penso, 2012.

Artigo: INTELIGÊNCIA ARTIFICIAL E APRENDIZAGEM PERSONALIZADA A DISTÂNCIA: CAMINHOS PARA A AUTONOMIA E EFICIÊNCIA NO MODELO 1:1

Vol. 1 2025

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Published

2025-09-11

Issue

Vol. 1 2025

Section

Comments and Essays

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How to Cite

Artificial intelligence and personalized distance learning: paths to autonomy and efficiency in the 1:1 model. (2025). Journal of Applied Education, 1(1). https://jedap.com.br/index.php/jornaldeeducacaoaplicada/article/view/27