A Case Study of an Extracurricular Program to Enhance University Students' Data Analysis and Artificial Intelligence Utilization Skills: Focused on the case Mentoring program

This study conducted and evaluated an extracurricular program aimed at improving university students’ skills in data analysis and artificial intelligence. Overall satisfaction with the program increased from 4.28 to 4.42, which is significant for enhancing students’ willingness to participate again and recommend it to others. By introducing a faculty advisor system, the systematic management and supervision of the mentoring program were strengthened through review and feedback on mentors’ activity reports, improving the program’s effectiveness. Additionally, through competitions, participants enhanced their practical problem-solving skills and their understanding and proficiency in Python and AI. Furthermore, students reported learning ‘integrative competencies utilizing diverse majors and backgrounds’, ‘self-directed learning skills’, ‘collaboration and interpersonal skills’, and ‘creative problem-solving skills’ through the program. It is recommended to consider the difference in learning levels between mentors and mentees during program operation, adjusting mentoring methods or difficulty levels, and systematizing mentor selection criteria. This study aims to provide practical directions for future program improvements. By doing so, it intends to contribute to strengthening the connection between the university’s general education and major education programs.