Enhancing Life Skill Progression and Psychological Well-being of Undergraduate Students through AI-driven Recommendation System

Abstract

Professionals may keep up with changed work settings and difficulties by continuing their education throughout their lives. Given the variety of courses offered, it is critical for professionals to have mechanisms that can connect them to appropriate programs. Although there is little information available regarding how teenagers utilize these courses, smartphone delivered life competency courses are a new and potential approach to support psychological wellness and discourage addiction to substances among young people. This paper explores the integration of AI-driven recommendation systems (AI-RSs) to enhance the mental health and professional skills of undergraduate students. Leveraging machine learning (ML) techniques and ontological frameworks, the proposed system aims to provide personalized recommendations for lifelong learning courses. By understanding individual preferences and learning objectives, the system facilitates the discovery of relevant courses tailored to the unique needs of students. This approach not only supports the continuous development of professional skills but also contributes to promoting mental well-being by fostering a sense of purpose and accomplishment through lifeskills learning. Through this abstract, we delve into the potential of AI-driven technologies to revolutionize education and support the holistic growth of undergraduate students.