Integration of artificial intelligence in formative assessment processes: implications for the continuous improvement of student performance

Abstract

Formative assessment plays a crucial role in enhancing learning by providing continuous feedback that guides and strengthens students' academic performance. In this context, the integration of artificial intelligence (AI) emerges as an educational innovation with significant potential to transform evaluation processes. This study analyzes the benefits, limitations, and pedagogical implications of applying AI-based tools in Latin American educational settings, focusing particularly on their impact on immediate feedback and personalized learning. A qualitative methodology was used through a systematic literature review, collecting evidence from twelve studies conducted in countries such as Ecuador, Mexico, Peru, Colombia, and Argentina. The findings show that AI improves the efficiency of educational diagnosis, accelerates pedagogical decision-making, and fosters student autonomy. However, challenges related to technological infrastructure, teacher training, and the need for solid ethical frameworks were also identified. It is concluded that AI should be conceived as a complementary tool, integrated into a hybrid assessment model that combines automation with professional teaching judgment. Finally, recommendations are proposed for educational institutions, policymakers, and academic communities aimed at ensuring a responsible, inclusive, and context-sensitive implementation