The Impact of AI-Driven Personalized Learning Platforms on Student Engagement and Academic Performance in K-12 Education

Abstract

This study investigates the impact of Artificial Intelligence (AI)-driven personalized learning platforms on student engagement and academic performance within the K-12 education sector. As traditional instructional models often struggle to accommodate diverse learning paces, AI integration offers a dynamic alternative by tailoring educational content to individual learner needs. Using a quasi-experimental research design, the study compares an experimental group utilizing AI-based platforms with a control group following a traditional curriculum over one academic semester. Data collection involves pre- and post-tests to evaluate academic growth, supplemented by standardized scales and platform analytics to measure behavioral and cognitive engagement. The expected results suggest that AI-driven personalization significantly enhances student involvement and leads to measurable improvements in academic achievement, particularly in core STEM subjects. These findings aim to provide critical insights into the efficacy of adaptive technologies in fostering more inclusive and effective learning environments.