DOI: https://doi.org/10.63345/ijre.v14.i6.3
Er. Aman Shrivastav
ABESIT Engineering College
Ghaziabad, India
Abstract
Advances in artificial intelligence (AI) are transforming K–12 education by enabling highly individualized instructional experiences that respond in real time to each student’s unique learning profile, preferences, and pace. Over the past decade, the convergence of large-scale educational datasets, sophisticated machine learning algorithms, and cloud‑based delivery has made it feasible to bring adaptive tutoring—once limited to proprietary research labs—into mainstream classrooms. This expanded abstract delves deeply into the mechanisms and impacts of AI‑powered personalization over a six‑month deployment across diverse urban and suburban schools serving grades 4–8. We explore the full cycle of diagnostic assessment, dynamic content sequencing, formative feedback, and progress visualization, showing how each component leverages probabilistic modeling, natural language processing, and reinforcement‑learning strategies to optimize learning pathways. Detailed quantitative analyses reveal that adaptive interventions yielded a 14–18% gain in standardized mathematics scores and a 10–13% gain in reading comprehension, with effect sizes ranging from moderate to large (Cohen’s d = 0.70–0.90). Qualitative data capture student and teacher experiences, highlighting enhanced motivation, self‑regulated learning behaviors, and productive teacher facilitation practices. The abstract further outlines considerations for ethical deployment, including transparency of recommendation logic, mitigation of algorithmic bias, and data‐privacy safeguards under FERPA and COPPA. Finally, we discuss scalability challenges—such as infrastructure requirements, teacher professional development, and equitable access—and propose a roadmap for sustained research to evaluate longitudinal learning gains, cross‑domain transfer, and the long‑term evolution of learner profiles. This comprehensive abstract sets the stage for a detailed exploration of both empirical outcomes and pedagogical implications presented in the manuscript.
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