Abstract:

The European Space of Higher Education clearly involves a profound change in both learning and teaching processes. Firstly, the subjects must be conceived as a set of abilities the students must achieve. Secondly, a mixture of methodologies and activities must be efficiently engaged to make students satisfactorily reach such abilities. Finally, several evaluation strategies must be carefully designed to obtain reliable information about the students' skills in terms of the abilities they must reach.
This paper focuses on the second goal. Great efforts are made to improve the quality of teaching methods. So far, the students have spent most of the time being taught in a large group. They study several contents and a final evaluation takes place. In general, only individual tuitions have allowed lecturers to interact with students, but lecturers hardly ever have information about the whole learning process of each student. Seminars, tutorials or workshops are some methodologies that have demonstrated success in developing abilities such as planning and managing their own learning, discuss topics or acquiring knowledge or getting projects off the ground. Particularly, they enhance and encourage certain abilities that companies used to demand from university graduates, like dynamism, communication, critical skills or customer interaction, in short, abilities related to team work. Fortunately, nowadays, we have at one’s disposal technologies provided by the Web 2.0 that facilitate interactivity. Despite of that the traditional face-to-face meeting must not be taken away.
A workshop or seminar could be defined as a scenario where both students and lecturers deal with a specific topic in depth. This active and shared participation entails a careful organization and design, establishing the necessary conditions to promote its correct development. Besides, it is necessary to ensure that the number of participants is not too large to facilitate the interaction. The organizational aspects this paper makes emphasis on are related to the distribution of the students rather than the methodologies. Particularly, the goal is to organize them according to the topics to deal with, which will be selected depending on the interests and/or weaknesses of the students. The method proposed in this paper automatically performs a distribution of the students according to their profiles, grouping them with similar preferences and learning difficulties. This task is performed using a machine learning approach taken from the artificial intelligence field which feeds on the marks and topic preferences of the students. The goal of building such profiles is to carefully select adequate topics to be candidates for the seminars. Sometimes, it happens that more than one topic might be appropriate to deal with during a seminar. A priori, one can choose the most voted topics, but if the majority prefers certain topic, it is desirable that certain seminar only copes with that one. But, if the preferences of the topics are more balanced, then dealing with more than one topic will be the best option. The proposal applies the D’Hondt law, commonly used in electoral processes, in order to select appropriate topics for both situations. The results obtained can be either a guarantee of what the lecturers could observe during the development of the course or a clue to reconsider new methodological strategies in certain topics.

Keywords:

seminars, clustering.