This study investigates the effectiveness of Octo-Focus, a novel AI-driven coaching system designed to enhance students’ self-regulated learning. Contemporary students increasingly struggle with distraction, procrastination, and ineffective study planning, which negatively impact academic performance. To address these challenges, Octo-Focus integrates AI-supported personalized planning, real-time focus and fatigue detection using Computer Vision, and behavioral analytics into a unified study support platform. A mixed-method approach was employed, combining survey data from secondary and higher education students with performance evaluations of a deep learning–based attention detection model. The results demonstrate that the proposed system reliably identifies attention and fatigue states with high accuracy and supports more structured, goal-oriented study behaviors. The findings suggest that Octo-Focus contributes a novel, holistic approach to digital learning support by transforming studying from a passive process into an adaptive, data-driven coaching experience.