Application of binary logistic regression in education assisted by artificial intelligence

Advances and Challenges of AI in the University Context: An Empirical Study

Authors

DOI:

https://doi.org/10.5007/1518-2924.2025.e101000

Keywords:

Artificial Intelligence, Digital Skills, Higher Education, Personalised Learning

Abstract

Objective: To predict whether university students will make efficient use of Artificial Intelligence (AI) in the coming years.

Method: A binary logistic regression is used, a statistical analysis that allows predicting the outcome of a binary dependent variable, in this case, the efficient use of AI, based on several independent variables, such as digital skills management or the use of Chat GPT.

Results: Social Sciences students have the lowest probability of using Chat GPT efficiently, and younger students are the ones who use AI the least effectively. Those students who use this tool professionally also show less efficient use, possibly because their professional focus limits the exploration of other uses. Good handling of the tool explains the efficient use of Chat GPT. Variables indicating inefficient use include the lack of digital skills or age.

Conclusions: It is essential to promote responsible and conscious use of AI in the educational field, encouraging innovative teaching methods that cater to the needs of students less familiar with AI, so that all students, regardless of their age, gender, or field of study, can benefit from what AI has to offer.

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Author Biographies

Angel Bartolome Muñoz de Luna, Universidad San Pablo CEU

Professor Dr. Ángel Bartolomé, from the San Pablo CEU University, is a doctor in communication, director of the CEU Publicis Master in Advertising Creativity and Innovation. Vice Rector of CEU Students. Master in EOI design management. Certified Teacher in Soft skills from the University of North Carolina (USA). Researcher in 12 competitive projects. Technology project manager and founder of Welvi Eperience (airfit). Art director at different advertising agencies. Doctoral thesis director.

 

For more information about his career, see: https://dialnet.unirioja.es/servlet/autor?codigo=2646217 https://scholar.google.es/citations?user=YQ2JIDQAAAAJ&hl=es

 

https://orcid.org/0000-0001-7056-8855

Sonia Martin Gomez, University San Pablo CEU

Dr. Sonia Martín Gómez has been a professor at the San Pablo CEU University since 1994. Responsible for the undergraduate Values ​​and Leadership Degree and the postgraduate Transformative Competencies Program. Project advisor at the RED Research Group, University of Antioquia, staying and directing thesis at said university. Award for application of new technologies in teaching and Award for innovation in Company Operational Management at USP-CEU. Author of application manuals.

For more information about her career, see: https://www.researchgate.net/profile/Sonia-Martin-Gomez https://dialnet.unirioja.es/metricas/investigadores/555443

https://orcid.org/0000-0002-9377-1941

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A capa da Revista ENCONTROS BIBLI apresenta como título do volume 30 do ano 2025 "Por uma ciência diversa, equitativa, inclusiva e acessível." Visualmente, a imagem destaca várias silhuetas de perfis de rostos humanos, representando diversidade, com diferentes tons de pele. À direita, há uma representação do globo terrestre. Na parte inferior da capa, são exibidas informações institucionais: "Departamento de Ciência da Informação, Programa de Pós-graduação em Ciência da Informação, Portal de Periódicos UFSC." A publicação é datada de 2025, Volume 30, ISSN 1518-2924.

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Published

2025-03-17

How to Cite

LUNA, Angel Bartolome Muñoz de; MARTIN GOMEZ, Sonia. Application of binary logistic regression in education assisted by artificial intelligence: Advances and Challenges of AI in the University Context: An Empirical Study. Encontros Bibli: revista eletrônica de biblioteconomia e ciência da informação, [S. l.], v. 30, p. 1–22, 2025. DOI: 10.5007/1518-2924.2025.e101000. Disponível em: https://periodicos.ufsc.br/index.php/eb/article/view/101000. Acesso em: 27 mar. 2025.

Issue

Vol. 30 (2025): For diverse, equitable, inclusive, and accessible science

Section

Dossier: News scenarios of the Digital Society and the challenges of Generative Artificial Intelligence

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Copyright (c) 2025 Angel Bartolome Muñoz de Luna, Sonia Martin Gomez

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