AI-Powered Academic Mentorship Systems: A Survey on Personalized Learning, Performance Analytics, and Intelligent Mentoring Platforms

Abstract

Artificial Intelligence (AI) is transforming the education sector by enabling intelligent learning environments, automated academic support, and data-driven decision-making. In recent years, various AI-based educational systems have been developed to improve personalized learning, mentorship, student engagement, and academic performance analysis. This survey paper reviews recent research in key areas such as AI-driven mentorship platforms, adaptive learning systems, educational data mining, performance prediction models, and emotion-aware interaction systems. A comparative analysis of existing studies highlights the techniques, methodologies, advantages, and limitations associated with these approaches. The survey further identifies major research gaps, including the lack of integration between mentorship systems, academic analytics, predictive modeling, and interactive engagement mechanisms. The findings of this study emphasize the growing importance of intelligent and integrated educational technologies for enhancing learning experiences and supporting academic development