Explainable AI-Driven Learning Ecosystems and Emerging Technologies for STEAM Education

<jats:p>The development and integration of artificial intelligence in education, such as the STEAM model, is driving the growth of smart learning environments; unfortunately, many of these systems have shortcomings and limitations in their learning models regarding transparency, interpretability, and the ability to understand decision-making and evaluation processes; this is particularly important for STEAM ecosystems, where results must be understandable, transparent, and justifiable for learning. The objective of this study is to analyze the use and applications of explainable artificial intelligence in the design, development, and use within STEAM educational ecosystems. The methodological approach involves a conceptual, documentary, and comparative analysis of the technologies, applications, approaches, models, and techniques of explainability in STEAM education found in the literature. The incorporation of various mechanisms, techniques, and combinations of models enables transparency and contributes to the understanding of the models and processes that support learning.</jats:p>