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

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.