AI-DRIVEN PERSONALIZED LEARNING IN BUSINESS EDUCATION

Abstract

The integration of artificial intelligence (AI) into business education has transformed traditional pedagogical approaches by enabling personalized learning experiences tailored to individual student needs. This study explores the efficacy of AI-driven personalized learning systems in enhancing student engagement, knowledge retention, and skill development in business education. Utilizing adaptive algorithms, machine learning models, and data analytics, these systems dynamically adjust content delivery, assessment methods, and feedback mechanisms to align with learners’ unique profiles, including their prior knowledge, learning pace, and career goals. A mixed-methods approach, involving quantitative performance metrics and qualitative student feedback, was employed to evaluate outcomes across a cohort of 250 undergraduate business students. Results indicate a 32% improvement in knowledge retention and a 45% increase in student satisfaction compared to conventional teaching methods. Furthermore, AI-driven systems fostered critical thinking and decision-making skills by simulating real-world business scenarios tailored to individual learner contexts. Challenges, such as data privacy concerns and the need for instructor training, were identified as barriers to widespread adoption. This research underscores the potential of AI to revolutionize business education by creating inclusive, adaptive, and outcome-oriented learning environments.