The Impact of AI-Based Learning Platforms on Students' Academic Achievement in Urban High Schools in South Korea
Keywords:
artificial intelligence, learning platforms, academic achievement, South KoreaAbstract
This study investigates the impact of artificial intelligence (AI)-based learning platforms on students' academic achievement in urban high schools across South Korea. Using a quasi-experimental design, the research compared academic performance, engagement levels, and learning outcomes between 450 students using AI-based platforms and 430 students receiving traditional instruction across eight urban high schools in Seoul, Busan, and Incheon over one academic year. Quantitative data were collected through pre-and post-tests, platform analytics, and standardized achievement measures, while qualitative insights were gathered through student surveys and teacher interviews. Results revealed that students using AI-based platforms demonstrated significantly higher academic achievement gains (mean difference = 12.7%, p < 0.01) compared to control groups, with particularly pronounced effects in mathematics and science subjects. Three key mechanisms emerged: personalized learning pathways that adapted to individual student needs and pacing, immediate feedback systems that enhanced metacognitive awareness and error correction, and increased student engagement through gamification and interactive elements. However, the study also identified important moderating factors including prior digital literacy, socioeconomic status, and teacher implementation fidelity that influenced effectiveness. Findings suggest that AI-based learning platforms offer substantial potential for enhancing academic achievement in technology-rich educational environments, but successful implementation requires adequate teacher training, equitable access to technology, and pedagogical integration that complements rather than replaces quality instruction. This research contributes to understanding AI's role in contemporary education and provides evidence-based recommendations for educational technology adoption in secondary schools.
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