%0 Journal Article
	%A J.R. Quevedo and  E. Montañés and  J. Ranilla and  A. Bahamonde
	%D 2009
	%J International Journal of Educational and Pedagogical Sciences
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 30, 2009
	%T Automatic Choice of Topics for Seminars by Clustering Students According to Their Profile
	%U https://publications.waset.org/pdf/7099
	%V 30
	%X The new framework the Higher Education is
immersed in involves a complete change in the way lecturers must
teach and students must learn. Whereas the lecturer was the main
character in traditional education, the essential goal now is to
increase the students' participation in the process. Thus, one of the
main tasks of lecturers in this new context is to design activities of
different nature in order to encourage such participation. Seminars
are one of the activities included in this environment. They are active
sessions that enable going in depth into specific topics as support of
other activities. They are characterized by some features such as
favoring interaction between students and lecturers or improving
their communication skills. Hence, planning and organizing strategic
seminars is indeed a great challenge for lecturers with the aim of
acquiring knowledge and abilities. This paper proposes a method
using Artificial Intelligence techniques to obtain student profiles
from their marks and preferences. The goal of building such profiles
is twofold. First, it facilitates the task of splitting the students into
different groups, each group with similar preferences and learning
difficulties. Second, it makes it easy to select adequate topics to be a
candidate for the seminars. 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.
	%P 674 - 678