Article

Empirical Study on Artificial Intelligence in Education and Its Influence on Learning Performance and Teaching Efficiency

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Abstract

The rapid advancement of Artificial Intelligence (AI) has transformed the educational landscape by reshaping how knowledge is delivered, processed, and assessed. This study investigates the relationship between AI adoption and learning effectiveness, focusing on variables such as learning outcomes, teacher productivity, and student engagement from 2018 to 2025. Using quantitative analysis based on trend evaluation and correlation modeling, the findings reveal that AI adoption in education shows a strong positive relationship with improved learning performance, higher teacher productivity, and enhanced student engagement. Statistical results indicate nearly perfect correlations (r > 0.98) among AI-related educational factors, suggesting that AI integration generates comprehensive benefits across multiple dimensions of teaching and learning. The study concludes that the effective implementation of AI technologies, including adaptive learning systems, intelligent tutoring, and automated assessment tools, can significantly enhance educational efficiency and personalization. These results highlight AI not merely as a technological innovation but as a catalyst for pedagogical transformation toward more adaptive, data-driven, and learner-centered education systems.

Keywords: Artificial Intelligence, Learning Outcomes, Educational Technology, Student Engagement, Teacher Productivity

How to Cite:

Fahmi, G. M., (2026) “Empirical Study on Artificial Intelligence in Education and Its Influence on Learning Performance and Teaching Efficiency”, Artificial Intelligence in Learning 2(1). doi: https://doi.org//AIL.122