Student Mobility Management System and Business Intelligence Solution for Higher Education Institutions

Abstract

Erasmus+ is a form of mobility supported by the European Union that provides education and internship opportunities at another contracted university abroad, subject to the agreements that university students and even faculty must adhere to. This way, international education opportunities are provided, and in addition to cultural exchange and integration, the goal is to increase international cooperation. This mobility is critical to its students' career development. While managing student mobility is straightforward for universities with a small number of programs, it can become complicated and time consuming for universities with a large number of faculties and institutes, and thus students. Our study proposes an information system for managing this complexity effectively. Prior to modeling, the developed information system was successfully run, with the goal of managing the process effectively. The study shares user experiences, critical points in the needs analysis process, developed processes and user roles, as well as screenshots of developed systems and their tasks. The findings indicated that administrators in universities welcomed such practices, and that effective management was provided for universities with intensive programs, particularly those with difficult-to-coordinate and dispersed campuses. By incorporating business intelligence technology into the developed system, it is ensured that educational technologies used in higher education institutions are up to date. No study has been identified in the literature that comprehensively evaluates the learning mobility process and connects the subject to current technologies.

Analysing Students’ Mobility at Higher Education Institutions: Case of Ukrainian University During the War

“…The investigated NaUKMA case demonstrates that data mining and analytics on students' mobility is not a management priority. Moreover, literature search returns only scarce publications on using education data mining to analyse students' academic mobility (e.g., Damar, 2022), mostly concentrating on students' educational performance for the drop-out prediction or internal specialty mobility. However, the absence of such work threatens the university's existence.…”