Utilization of Artificial Intelligence in Improving Student Achievement

Abstract

This study investigates the transformative potential of Artificial Intelligence (AI) in higher education, focusing on its impact on student achievement, equity, and systemic educational improvements. It explores how AI facilitates personalized learning, addresses educational disparities, and aligns academic outcomes with societal and workforce demands. A qualitative approach using a Systematic Literature Review (SLR) method was employed to synthesize insights from recent peer-reviewed studies. The research analyzed the integration of AI into higher education, examining pedagogical strategies, systemic challenges, and ethical considerations. The findings reveal that AI significantly enhances student engagement and academic performance by personalizing learning experiences. It also supports educators by automating routine tasks, enabling more focused student interaction. AI can potentially democratize access to quality education, particularly in underserved regions. However, challenges such as resistance to change, technological infrastructure limitations, and ethical concerns related to data privacy and algorithmic bias were identified. The discussion emphasizes the need for ethical frameworks and inclusive policies to ensure effective and responsible AI integration. This study provides practical insights for universities, policymakers, and technology developers. Institutions are encouraged to invest in infrastructure, align curricula with AI advancements, and train educators in AI applications. Policymakers should support digital literacy initiatives and equitable technology access. These measures highlight AI’s capacity to create more inclusive, adaptive, and sustainable higher education systems, underscoring its transformative role in modern education.