Artificial Intelligence in Education: Bridging Technology and Pedagogy for Student-Centered Outcomes

Abstract

The integration of Artificial Intelligence (AI) into education has catalyzed a paradigm shift from traditional, teacher-centered instruction to adaptive, personalized, and student-centered learning models. This study examines the impact of AI-driven Intelligent Tutoring Systems (ITS) on education, employing a mixed-methods approach. Results from 200 students show a statistically significant improvement in learning outcomes for the ITS group, with post-test scores rising from 61.23 to 82.43 (t = 13.01, p < 0.002). Engagement levels were also significantly higher (mean = 5.42 vs. 3.21), with 76% of ITS users reporting high engagement. These gains are attributed to personalized learning, real-time feedback, and emotion-aware AI. However, challenges such as algorithmic bias, data privacy, and the digital divide highlight the need for ethical, inclusive, and human-centered AI design. The study concludes that ITS should augment, not replace, teachers, ensuring equitable and effective integration of AI in education. Despite these benefits, the study identifies critical challenges, including algorithmic bias, data privacy concerns, and the digital divide, which threaten equitable access and ethical integrity. The findings advocate for a human-centered AI approach, where intelligent tutoring systems augment rather than replace the role of educators. The paper concludes with policy and design recommendations for the responsible integration of AI in education, emphasizing transparency, inclusivity, and ethical governance. By aligning technological innovation with pedagogical principles, AI-powered ITS can transform education into a more inclusive, adaptive, and practical experience for all learners.