Competence profile differences among graduates from different academic subject fields: implications for improving students’ education

The aim of a university education is the intellectual development of citizens, and the training of professionals for their subsequent entry into the workforce. However, this entry into the workforce, following the theoretical education usually provided by the university, implies that students have to manage this difficult transition by themselves. Society, in a continual process of transformation, requires of universities that they adjust, adapting the education they offer to comply with the demands of society and the workplace. Socio-emotional skills would seem to have influence predicting professional performance. These skills also influence job-finding and employability. Consequently, providing teachers with an education in socioemotional competences is becoming a necessary task within universities, and the majority of teaching staff consider these skills to be fundamental to the personal and socio-emotional development of students. The objective of our proposed work is to establish the characteristic profile of competences of a sample of teachers in training, and compare it with the competences profile of graduate students belonging to the fields of law sciences, social sciences, humanities, science and technology, and health. Starting from results, implications will be derived for the development of generic competences of socio-emotional type in the framework of the European Frame of Higher Education.

Serve analysis of professional players in beach volleyball

This study has been developed for the European Beach Volleyball Championship in 2005. The video-recorded analysis was held using Sportcode Pro v.8.5.2 software. The aim of study was to determine the types of serve used, depending on the time of the set in which they occur. Quantitative analysis with a sample of 10 players that make up 5 teams with a total of four meetings with a total of 327 serves analyzed. The serves were classified depending on the period which they occurred, the period being 1 (items 1 to 7), period 2 (from point 8 to 14) and period 3 (point 15 to 21). he statistical analysis was conducted using the statistical software SPSS 19, Chi-square test established significant differences between the different types of serve for period 1 and 2 (p<0.05), but no significant differences were established in the period 3 to floating serve and power jump (p>0.05). The results showed a decrease of using a serve with jump power at period 1 (89.7%) compared to the period 3 (27.3%), while the floating and floating serve jump respectively increase at period 1 (6.3% -4%) in the period 3 (23.4% -49.4%).