The integration of Artificial Intelligence (AI) into educational systems has revolutionized personalized learning. This study aims to evaluate the effectiveness of AI-driven platforms (such as adaptive learning systems) on the mathematical proficiency of secondary school students. Using mathematical modeling, specifically focusing on growth curves and proficiency variables, the research analyzes data from experimental and control groups. The results indicate that AI platforms facilitate a non-linear acceleration in knowledge acquisition by addressing individual learning gaps in real-time. The study concludes that AI-based intervention significantly shifts the mean proficiency levels and optimizes the learning trajectory of students with diverse cognitive starting points.

Artificial Intelligence in Education (AIEd), Mathematical Modeling, Adaptive Learning, Proficiency Growth, Pedagogy, STEM, Data Analysis.

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