Classrooms Without Walls: How AI Personalizes Each Student's Learning

Aulas Sin Muros: Cómo la IA Personaliza el Aprendizaje de Cada Estudiante

Abstract

Artificial Intelligence (AI) is transforming contemporary education, creating “classrooms without walls” that transcend traditional limitations. This research assumes a critical yet optimistic perspective to analyze how AI personalizes individual learning, contrasting diverse theoretical positions. In this context, Cisneros, Nevárez, Farez and Torres (2024); adopt a favorable stance by asserting that AI enables effective adaptation of content to individual characteristics, while López, Rivera and Cruz (2023); empirically demonstrate significant improvements through personalized learning systems, documenting quantifiable increases of 30-50% in knowledge retention. This optimistic vision contrasts with the more cautious position of Pinela (2024); who identifies multidimensional challenges that require robust ethical frameworks. For their part, Demartini, Sciascia, Bosso and Manuri (2024): emphasize an evidence-based perspective, arguing that technology should enhance human capabilities without substituting fundamental elements of integral development. The critical analysis distinguishes between real benefits and inflated commercial expectations. The conclusions confirm that classrooms without walls represent a conditional transformative opportunity: their success depends on the balance between technological innovation and preservation of humanistic values.