Application of artificial intelligence in education: models and tools to predict and improve academic performance towards an SDG perspective

The application of artificial intelligence (AI) in education is analyzed, focusing on how various models and algorithms can predict and improve academic performance, in line with the Sustainable Development Goals (SDGs). A documentary and comparative approach was used to analyze recent research on machine learning techniques or algorithms, such as neural networks, SVM, KNN and decision trees, among others that are applied to the detection of underachievement and school failure. Tools that allow monitoring and anticipating academic performance were also reviewed. AI has a high potential to identify academic risk patterns, facilitating early interventions. If implemented ethically and strategically, it can contribute significantly to inclusive and quality education, supporting the achievement of the SDGs.

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Publication Details

Journal
International Journal of Combinatorial Optimization Problems and Informatics.
Published
2025-07-14
DOI
https://doi.org/10.61467/2007.1558.2025.v16i3.1131
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.00
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article

Application of artificial intelligence in education: models and tools to predict and improve academic performance towards an SDG perspective

Ricardo A. Barrera-Cámara, Ana Canepa Saénz, Miguel Gonzalez, Fernando E. Sánchez-Martínez
International Journal of Combinatorial Optimization Problems and Informatics.
Online Learning and Analytics
article

Application of artificial intelligence in education: models and tools to predict and improve academic performance towards an SDG perspective

Ricardo A. Barrera-Cámara, Ana Canepa Saénz, Miguel Gonzalez, Fernando E. Sánchez-Martínez
article en

Abstract

The application of artificial intelligence (AI) in education is analyzed, focusing on how various models and algorithms can predict and improve academic performance, in line with the Sustainable Development Goals (SDGs). A documentary and comparative approach was used to analyze recent research on machine learning techniques or algorithms, such as neural networks, SVM, KNN and decision trees, among others that are applied to the detection of underachievement and school failure. Tools that allow monitoring and anticipating academic performance were also reviewed. AI has a high potential to identify academic risk patterns, facilitating early interventions. If implemented ethically and strategically, it can contribute significantly to inclusive and quality education, supporting the achievement of the SDGs.

International Journal of Combinatorial Optimization Problems and Informatics.Vol. 16(3)
Universidad Autónoma del Carmen (MX), Universidad Politécnica de Pachuca (MX), El Colegio de Morelos
Openalex Percentile: Top 82%
Online Learning and Analytics
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Application of artificial intelligence in education: models and tools to predict and improve academic performance towards an SDG perspective — Ricardo A. Barrera-Cámara, Ana Canepa Saénz, et al. · International Journal of Combinatorial Optimization Problems and Informatics. (2025) | TGRS Research Map | TGRS