Educational analytics and data-driven pedagogical management: models, benefits, and challenges in Latin America

Digital transformation and access to large volumes of data have reshaped educational management in Latin America, challenging traditional models based on subjective perceptions. This paper analyzes how data-driven educational management models contribute to educational decision-making and improved academic performance, with an emphasis on Latin America and the Dominican Republic. A descriptive-analytical design with a qualitative approach was used, based on a systematic review of scientific and institutional literature (2019–2024), including sources from Dialnet, SciELO, and Google Scholar. Key benefits were identified, such as more objective decision-making, real-time monitoring, and personalized learning. Initiatives such as SIGERD in the Dominican Republic and experiences in Brazil, Chile, and Mexico have demonstrated positive impacts on educational efficiency and equity. Educational analytics strengthens school management by transforming data into effective pedagogical actions. However, challenges persist, such as the digital divide, teacher training in analytical skills, and ethical data use. Artificial intelligence is projected to play a growing role in the future of data-driven education.