Conference Agenda
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
Please note that all times are shown in the time zone of the conference. The current conference time is: 24th Aug 2026, 06:26:45am America, Santiago
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Daily Overview |
| Session | |
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32D: Engineering Education Virtual location: VIRTUAL: Agora Meetings | |
| Presentation 1 | |
10:20am - 10:28am
Development of an intelligent software architecture for the pre-professional practices of a public university Universidad Nacional Federico Villarreal, Perú The management of pre-professional internships in public universities is a key process for professional training; however, it is often carried out using manual procedures or fragmented systems that generate delays, limited traceability, and a progressive decrease in student satisfaction. The objective of this study is to propose an intelligent software architecture that optimizes the management of pre-professional internships in an engineering faculty of a public university, addressing the main operational limitations of the current process. The method is applied research using an agile methodology called Rational Unified Process, based on the analysis of the internship administrative process, the application of questionnaires to 52 students, and the gathering of functional and non-functional requirements. These inputs allowed for the design of an architecture based on the Model-View-Controller pattern and a microservices-oriented approach. The results show that, although 84.6% of students value the treatment they receive from administrative staff positively, overall satisfaction with the process reaches only 73.1%. Weaknesses were identified in response times, report review, and the assignment of faculty reviewers. Furthermore, differences were observed between academic departments, with satisfaction levels dropping to 66.7%, and a progressive reduction among recent graduates, from 72.7% in 2024 to 62.5% in 2025. Conclusion, the study demonstrates that the proposed intelligent software architecture constitutes a viable technical solution with the potential to significantly improve the efficiency, traceability, and quality of pre-professional internship management in public universities. | |
