Enhancing Education for Undergraduate Students of Computer Science through Mentoring: A Big Data Analytics Approach

Abstract

In the arena of computer science tutoring at the undergraduate level, mentorship programs have become an essential tool for professional and academic growth. This study examines the critical role that mentoring plays in improving computer science students' educational experiences and offers a cutting-edge strategy that makes use of big data analytics to maximize these mentorship programs. Educational institutions can obtain deeper insights into mentoring's impact on pupils' learning outcomes, skill development, and motivation by gathering and evaluating large amounts of data, including academic performance measures, program participation, and qualitative feedback. This data-driven strategy provides a road map for enhancing mentorship programs and, eventually, raising the standard of undergraduate computer science education, guaranteeing that students are equipped to tackle the demands of a quickly changing field. Sustainable Development Goal (SDG) 8 has also relevance with the enhancing education for students