Web site of university:
https://www.uniduna.hu/
Email: sitkuk@uniduna.hu
Established as the Technicum of Metallurgy and Mechanical Engineering in 1953 to provide skilled workforce for the local steel industry, but diversifying its industrial partner portfolio after 2010, the University of Dunaújváros became a university of applied sciences on 1 January 2016, and operates as a foundation university today. Besides cherishing the 18th-century Selmecbánya Bergschola traditions, it has shown remarkable flexibility in adapting to the ever changing political and economic environment resulting in an independent institutional status and becoming a major professional higher education institution in Central Hungary. Its values of a strong, industry-oriented attitude, student-centered approach, and family-friendly practices serve to provide high-quality skilled workforce for the regional and national job markets in various engineering fields, business management, and communication and media sciences. Lately, it has won national renown by a unique inter-sectoral training career management programme for students from 15 to 99 years old, KÉP, which we present here.
Dimensions of community engagement |
Authenticity |
Social needs |
Communities |
Spread |
Sustainability |
---|---|---|---|---|---|
Teaching and learning |
|||||
Research |
|||||
Service and knowledge exchange |
|||||
Students |
|||||
Management / partnerships |
|||||
Management / policies |
|||||
Peer support |
Heatmap colour legend: |
Lowest level |
Highest level |
|||
The list below shows three institutions that have different results in their institutional heatmap (see methodological note*).
The list below shows three institutions that have different results in their institutional heatmap (see methodological note*).
* Methodological note:
The aim of this feature is to allow users to explore the variety of ways in which universities approach and organise community engagement, without allowing a direct/competitive comparison of performance. Similar and different institutions are automatically generated based on the results of their institutional community engagement heatmap results. The method used is applying Euclidean distance between institutions to provide the similar and differing institutions, which calculates the distance in an n-dimensional space between two cases.