SIMULATION MODELING FOR THE DIGITAL TRANSFORMATION OF THE HIGHER EDUCATION PROCESS MANAGEMENT SUBSYSTEM

Abstract

This paper presents an approach to the digital transformation of the higher education process management subsystem through simulation modeling. The proposed model captures the dynamic structure of the educational environment, incorporating key entities such as students, teachers, academic disciplines, study groups, class schedules, and administrative controllers. The architecture is implemented using the Python programming language in combination with the SimPy library, allowing the system to simulate event-driven interactions flexibly and scalable.

The simulation logic is based on a weekly academic cycle and includes processes such as attendance tracking, teaching load monitoring, scheduling conflicts resolution, and performance evaluation. A BPMN-based block diagram is provided to illustrate the system's logic, supported by fragments of code and parameterized settings. Initial conditions and simulation parameters are clearly defined to reflect realistic academic settings.

Several experimental scenarios are modeled, including teacher overload, room shortages, and overlapping schedules, with the aim of identifying system bottlenecks and testing adaptive responses. The results demonstrate that the simulation model enables early detection of critical areas in process planning and supports data-driven decision-making at the administrative level.

By combining simulation modeling techniques with adaptive control logic, this research offers a powerful tool for the analysis, optimization, and modernization of academic process management systems in higher education institutions. The approach enhances transparency, flexibility, and responsiveness of university operations within the context of ongoing digital transformation.