Application of Mobile Learning Platform in Intelligent Higher Education System

Abstract

This study investigates the use of mobile learning platforms within intelligent higher education systems, with an emphasis on the role of artificial intelligence (AI) in improving student learning experiences and outcomes. The research, which is based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model, looks into important notions including Performance Expectancy and Effort Expectancy to better understand students' views and actions toward mobile learning platforms. The study reveals insights into the revolutionary potential of AI-driven mobile learning platforms in facilitating personalized, adaptive, and interactive learning experiences by conducting a thorough examination of literature, case studies, and empirical data. AI algorithms evaluate student data to give personalized content, adaptive tests, and real-time feedback, whereas AI-powered chatbots offer on-demand support and advice. Furthermore, AI-powered analytics provide educators and administrators with actionable insights that enable informed decision-making and continual improvement. By combining theoretical frameworks, emerging trends, and practical experiences, the study provides actionable recommendations for effectively integrating AI in mobile learning platforms to advance intelligent higher education systems and foster inclusive and innovative educational practices in the digital age.