Advances and challenges of Artificial Intelligence in the university context: An empirical study

This study aims to predict whether university students will make efficient use of Artificial Intelligence (AI) in the coming years, using a statistical analysis that predicts the outcome of a binary dependent variable (in this case, the efficient use of AI). Several independent variables, such as digital skills management or the use of Chat GPT, are considered.The results obtained allow us to know that inefficient use is linked to the lack of digital skills or age, among other factors, whereas Social Sciences students have the least probability of using Chat GPT efficiently, and the youngest students are the ones who make the worst use of AI.

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Publication Details

Journal
Journal of Infrastructure Policy and Development
Published
2024-11-05
DOI
https://doi.org/10.24294/jipd.v8i13.8388
Citations
1
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.41
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article

Advances and challenges of Artificial Intelligence in the university context: An empirical study

Sonia Martín Gómez, Ángel Bartolomé Muñoz de Luna
1 citations
Journal of Infrastructure Policy and Development
Online Learning and Analytics
0.41
article

Advances and challenges of Artificial Intelligence in the university context: An empirical study

Sonia Martín Gómez, Ángel Bartolomé Muñoz de Luna
article en
1 citations

Abstract

This study aims to predict whether university students will make efficient use of Artificial Intelligence (AI) in the coming years, using a statistical analysis that predicts the outcome of a binary dependent variable (in this case, the efficient use of AI). Several independent variables, such as digital skills management or the use of Chat GPT, are considered.The results obtained allow us to know that inefficient use is linked to the lack of digital skills or age, among other factors, whereas Social Sciences students have the least probability of using Chat GPT efficiently, and the youngest students are the ones who make the worst use of AI.

Journal of Infrastructure Policy and DevelopmentVol. 8(13)
Universidad San Pablo (MX)
Quality Education
Openalex Percentile: Top 26%
Online Learning and Analytics
0.41
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