La inteligencia artificial como herramienta para el análisis del rendimiento estudiantil: una revisión desde la analítica del aprendizaje

Abstract

Artificial intelligence (AI) emerges as an innovative tool transforming education by offering new possibilities to analyse and enhance student performance. Its application in learning analytics enables the processing of large volumes of data and the detection of complex patterns that facilitate personalised learning and evidence-based decision-making. This allows for timely educational interventions tailored to the specific needs of each student, promoting more effective and motivating learning experiences. However, despite its benefits, the integration of AI in education faces significant challenges, such as the efficient management of academic information, data quality and availability, teacher training, and ethical concerns related to privacy and data security. A systematic literature review conducted through a qualitative approach and documentary methodology has identified the most commonly used techniques, such as neural networks and decision trees, as well as current applications, benefits, and limitations. Furthermore, the importance of establishing regulatory and pedagogical frameworks that ensure responsible and equitable use of AI is emphasised, guaranteeing that its integration contributes to the continuous improvement of educational quality and the holistic development of students. In summary, AI represents a significant opportunity to revolutionise education, provided that its challenges are adequately addressed and its potential fully harnessed.