An Agent-Based Model to Address the Gap in Internship Opportunities for IT Undergraduates in Sri Lanka
Internship opportunities are vital for IT undergraduates, bridging the gap between academic knowledge and practical skills. In Sri Lanka, the IT sector faces a significant mismatch between the demand for internships and the opportunities available. This study addresses the issue by developing an Agent-Based Model (ABM) using NetLogo to simulate interactions among students, universities, and companies. The model explores key factors such as student skills, university-industry collaboration, and company hiring preferences influencing internship allocation. The findings emphasize the importance of adaptability among students and companies in bridging the internship gap. High-performing students with strong GPAs were placed earlier in large companies, while others who adjusted their skills and salary expectations secured positions in smaller firms. Companies that relaxed hiring criteria, such as GPA thresholds, filled more positions, highlighting the need for flexibility. Disparities were observed between students from private and government universities, with private university students securing internships faster due to better resources and connections. This study underscores the importance of aligning academic curricula with industry needs, fostering skill development programs, and promoting collaboration between academia and businesses. Recommendations include financial incentives for small and medium-sized enterprises (SMEs) to provide internships and enhanced university resources to ensure equitable access. These insights can guide policymakers, universities, and companies in improving workforce readiness and addressing the internship gap for IT undergraduates in Sri Lanka.
Authors
- M.L.T. Kannangara
- Sandushi Weraduwa
- Nadeera Gayantha
- Kavindu Piyumantha
- Chathura Rajapaksa
Institutions
- University of Kelaniya (LK)
Publication Details
- Published
- 2025-02-19
- DOI
- https://doi.org/10.1109/icarc64760.2025.10963178
- Primary Topic
- Educational Technology and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00