COGNITIVE DYNAMICS AND NEURAL PLASTICITY IN PRESCHOOLERS: INTEGRATING ARTIFICIAL INTELLIGENCE ELEMENTS TO STIMULATE EARLY HEURISTIC LEARNING

Tleumbetova Kallygul

COGNITIVE DYNAMICS AND NEURAL PLASTICITY IN PRESCHOOLERS: INTEGRATING ARTIFICIAL INTELLIGENCE ELEMENTS TO STIMULATE EARLY HEURISTIC LEARNING

Tleumbetova Kallygul

Acting Professor of the Department of Preschool Education, Nukus State Pedagogical Institute named after Ajiniyaz

##semicolon## Cognitive activity, artificial intelligence in education, early childhood development, heuristic learning, adaptive algorithms, neuroplasticity, sustained attention.

सार

The integration of adaptive digital environments in early childhood education necessitates a rigorous evaluation of how algorithmic scaffolding influences primary neurodevelopmental milestones. This study quantifies the precise pedagogical and cognitive outcomes of utilizing artificial intelligence elements—specifically voice-assisted heuristic learning and adaptive pattern recognition algorithms—to stimulate intrinsic cognitive activity in early-stage learners. A quasi-experimental, prospective pedagogical analysis was conducted involving 112 preschool-aged subjects (5–6 years old) enrolled in preparatory educational pathways. Subjects were stratified into a conventional pedagogical cohort (n=54) receiving standard didactic instruction and a targeted experimental cohort (n=58) interacting daily with an AI-mediated adaptive curriculum designed to dynamically adjust cognitive load based on real-time user performance. Empirical data indicate that static, uniform teaching modalities frequently fail to sustain executive function in children with rapid neural plasticity. The AI-integrated cohort demonstrated a highly significant 34.2% acceleration in spatial working memory acquisition, directly correlating with an expansion of sustained attention spans from a baseline of 11.2 ± 1.4 minutes to 18.6 ± 1.8 minutes by week 12 (p = 0.011). Conversely, the conventional group exhibited persistent plateaus in heuristic problem-solving and a higher incidence of task-abandonment behaviors. The dynamics of the observed results suggest that artificial intelligence functions as a highly precise, individualized cognitive scaffold. Comprehensive early education frameworks must actively integrate these adaptive digital elements to continuously stimulate the zone of proximal development, preventing cognitive stagnation and optimizing the foundational architecture required for complex analytical reasoning.

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