Abstract:

The usage of ranking techniques to create league tables for universities is a current trend topic. The increase in the number of interconnected elements of the system (students, teachers, potential employers, grant funds) leads to an extreme diversity of potential patterns of communication. Informational globalization allows promoting a world-wide comparison of higher educational organizations as knowledge-transfer "hubs".

League tables have many advantages. First, they allow governments in particular, and society in general, to get more or less ‘politically’ independent and scientifically verified data on how effective the public spending is, in the sphere of higher education and how competitive is certain organization in world's education market. Second and even more important for the educational organizations, is that league tables can stimulate universities to empower some ‘public’ activities: knowledge sharing through scientific and educational webs (publications, conferences, creation of specialized web libraries, etc.), stimulation of student mobility, expansion of research programs.

There are a lot of critics to currently existing ranking systems. They argue that the list of control parameters that is used in them is not sufficient to allow the system be assessed as ‘perfect’ even for certain geographical regions, not to mention the whole world.

Rather than trying to figure out if the ranking for certain university is perfect, let us to consider how that rank influences on the education area as a whole from the sustainable development perspective. The following two questions illustrate the problem: “is it better the education area to have the one extremely strong university and a few weak ones or to have a several average instead”, “do the ranking coefficients need to be changed dynamically as a function of the current state of education market, or should they remain solid regardless of education state“.

We investigate how some mathematic and computer science models can help to resolve the aforementioned questions.

Keywords:

Webometric, ranking, sustainability, soft models, optimization, digital education management.