Designing an Algorithm for Promoting Mentor-Mentee Relationships: Enhancing the Learning Approach of Mentee

Relationships between mentors and mentees are crucial for fostering both intellectual and personal development. This study presents a new method that maximizes mentor-mentee matching using a recommendation system, hence improving the efficacy of these interactions. The algorithm makes sure that each student receives a personalized match that meets their specific needs by examining important variables including learning styles, interests, personal aspirations, and academic ambitions. The study investigates how data-driven approaches can enhance mental health, involvement, and general life happiness in addition to educational success. Learners' motivation and happiness are increased when they actively participate in the selecting process, which is made possible by the algorithm. The results of this study can help teachers and policymakers to make decisions that will encourage mentoring programs that assist students in all facets of their lives.