AI MENTOR FUNCTIONS IN SCALABLE ONLINE COURSES: OPPORTUNITIES AND LIMITATIONS

Abstract

The rapid expansion of online education has created an urgent need for scalable and efficient mentoring systems. Traditional instructor-led mentoring is insufficient to support the growing number of learners in Massive Open Online Courses (MOOCs) and other digital learning platforms. Artificial Intelligence (AI) mentors have emerged as a promising solution, offering personalized guidance, automated feedback, and real-time interaction at scale. This article explores the capabilities and limitations of AI mentor systems in scalable online education. The study incorporates statistical analysis, cost-efficiency calculations, and theoretical frameworks to evaluate their effectiveness. The findings suggest that AI mentors significantly enhance learner engagement, completion rates, and cost efficiency, but they also present challenges such as lack of emotional intelligence, algorithmic bias, and ethical concerns. The paper concludes with practical recommendations for integrating AI mentors into modern educational ecosystems through hybrid models.