Academic Success: tutoring and machine learning programs used to generate personal and professional development in university students

Authors

  • Luísa Raeder Ribeiro Universidade Federal Rural do Rio de Janeiro (DCAd.UFRRJ), Brasil Programa de Extensão DEGECAR (UFRRJ), Brasil https://orcid.org/0009-0007-6900-0702
  • Marco Aurélio Calandino Faria Junior Universidade Federal Rural do Rio de Janeiro (DCAd.UFRRJ), Brasil Programa de Extensão DEGECAR (UFRRJ), Brasil https://orcid.org/0009-0005-4919-9369
  • Marcello Vinicius Doria Calvosa Universidade Federal Rural do Rio de Janeiro (DCAd.UFRRJ), Brasil Grupo de Pesquisas GeCaPEP (CNPq), Brasil Programa de Extensão DEGECAR (UFRRJ), Brasil https://orcid.org/0000-0003-2724-9431

DOI:

https://doi.org/10.18540/jcecvl11iss1pp21443

Keywords:

Artificial Inteligence, Tutoring Program, Machine Learning

Abstract

The objective of this work was to prepare an academic and critical review based on the scientific article: Effectiveness of Tutoring at School: a machine learning evaluation, published in 2024, in English, in the scientific journal Technological Forecasting & Social Change. The article addresses central concepts, such as Artificial Intelligence and Machine Learning, in analyses of public policies and tutoring programs aimed at university students. As a main premise, the original work, through extensive quantitative research, demonstrates how supervision, support and guidance of students can reduce the chances of dropping out of studies and academic failure. Machine Learning, from the perspective of an analytical tool and methodological innovation, can, according to the article, influence and optimize student performance. The review contributes to undergraduate and graduate students seeking training in emerging technologies, developing skills in research topics and motivating the generation of skills in a scenario of high competitiveness and rapid technological evolution, so that they can achieve and sustain academic and professional success.

Keywords: Artificial Inteligence. Tutoring Program. Machine Learning.

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References

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Published

2025-02-24

How to Cite

Ribeiro, L. R., Faria Junior, M. A. C., & Calvosa, M. V. D. (2025). Academic Success: tutoring and machine learning programs used to generate personal and professional development in university students. The Journal of Engineering and Exact Sciences, 11(1), 21443. https://doi.org/10.18540/jcecvl11iss1pp21443

Issue

Section

General Articles