A Deep Learning Approach to Networking Education for Undergraduates Using Cisco Packet Tracer

Ascanoa L.; Garcia-Espinoza F.; Corimanya B.; Hidalgo-Aramburu F. · Proceedings - International Conference on Smart-Green Technology in Electrical and Information Systems, ICSGTEIS (2025) · DOI: 10.1109/icsgteis68532.2025.11284308

Resumen

This research proposes a pedagogical strategy for teaching computer networks to undergraduate students, grounded in a deep learning approach and the use of Cisco Packet Tracer as the primary tool. The methodology integrates repetitive practice, autonomous analysis, and problem-solving through simulations ranging from basic LANs to complex interconnections, later validated with physical laboratory equipment. Results indicate that 25% of students consider basic topology configuration straightforward, while 100% reported that the simulator significantly strengthened their theoretical and practical understanding. Furthermore, 91.67% acknowledged an improvement in problem-solving skills for complex scenarios. Although simulations stand out for their accessibility and ease of use, hands-on practice remains essential to consolidate technical skills. In this regard, 58.33% of students expressed a preference for combining virtual environments with physical devices. It is concluded that this integration enhances conceptual understanding, fosters autonomy, and improves academic performance

Instituciones: Universidad Ricardo Palma