Abstract:

One of the different measures for building the European Higher Education Area (EHEA) is the establishment of the European Credit Transfer System (ECTS). This system, based on the Socrates-Erasmus exchange programs, becomes a starting point for achieving a clear and common EHEA. Moreover, its application makes the education programs more comparable and understandable for all students, easing student exchange and academic validation. It also helps universities to organise and review their education programs, and makes the European Higher Education more attractive for students outside the EU.
The ECTS quantifies the student’s learning results or the competences that express what the student will know and understand; or problems that the students will be able to face after completing the learning process. In the ECTS, credits can only be obtained once the work required has been finished and the learning results evaluation properly carried out. The student’s results are documented by a local/national mark. Using an ECTS grading system is a good option for credit transferring. These ECTS grades use a statistical base for classifying the students, which constitute a previous requisite to apply in the ECTS evaluation system. This way, the marks are assigned to the passing students according to the following criterion: A for the first 10%; B the next 25%; C the 30% after; D the following 25% and E the final 10%.
In order to deal with the relation between the present credit system and the ECTS, a data base has been set up to gather grades, the name and type of subject, and the number of direct teaching hours as well as independent learning hours, for the four degrees (Agricultural Engineer, MSc in Food Science and Technology, Forest Engineer and MSc in Biotechnology) that can be earned in the School of Agricultural Engineering at the Universidad Politécnica of Valencia.
In order to properly study this huge data base has been analysed by means of latent structures based projection models. In this case, has been used the Partial Least Squares (PLS) model. Once the different variables have been analysed and once those showing a real influence on the final mark have been clarified, the corresponding relationship outlined by the PLS models has been studied and compared with average means graphs relative to the proportioned results of the PLS models.
The main conclusions of this study, for the grades analysed, is that some subjects, as well as their type are the variables really having an influence on the final mark. On the other hand, neither the ECTS credits nor the students’ dedication are having any type of influence.
These two conclusions imply that, firstly, some subjects need an extra effort in order to be passed whereas some others are too easy to pass and, secondly, the student’s dedication is not as effective as it should be, or that there exists too much variation in dedication between students.

Keywords:

education, experience, european credit transfer system.