USING FUZZY COGNITIVE MAPS FOR SELECTING COMPLEMENTARY SUBJECTS IN A PROFESSIONAL ACCREDITED MASTER – MASTER IN FORESTRY ENGINEERING
The European Union is an open market for workers and technicians, where professional accreditation is needed for applying in certain positions. In each European country, professional accreditation is provided either by professional associations or Government departments. Before applying for a job, workers had to obtain a bachelor degree or a master from an academic institution. Universities offer academic degrees and masters in response to an apparent demand and constraint to their resources, creating a wide range of titles and specialties. Usually, universities had reached an agreement with national accreditation agencies before building a master program. However, the increment in number of the European Union countries and the high frequency of studying abroad have generated a global academic market where it is unviable to state agreements every University with each European members.
The Bologna Declaration has promoted the convergence of the European Higher Education and, in this sense, has stimulated the characterization of curricula based on the concepts of level of competition and European credits (ECTS), which has simplified the way to compare academic qualifications. This synoptic characterization of the curriculum can also be used to facilitate professional accreditation agencies charged of analysing and validating academic title for professional use. Based on ECTS and academic programs some graph network analysis technics, as Fuzzy Cognitive Maps (FCM), can be used to optimize syllabus and student curriculum.
FCM is a graph directed method, formed by a set of nodes ("academic subjects") linked by arrows which symbolise knowledge transference between matters. To generate an FCM, first, the degree academic subjects are drawing. Secondly, each student evaluates the relationships between academic subjects in terms of knowledge transference. And then, methods of fuzzy logic are applied to quantify the degree of relationships between academic subjects. Finally, indicators of the flow of knowledge are obtained, which express synoptically the strength of every academic subject and therefore the subject importance into the academic degree.
The application of FCM for each student locates the shortages regarding the minimum professional requirements, facilitating the identification of necessary training to achieve a professional accreditation. In our work, we applied FCM to determine the best set of complementary subjects to choose when a Natural Environmental Engineering graduate student joins to the Master in Forestry Engineering from the Technical University of Madrid (UPM).