Differences between the personal, social and emotional profiles of teaching and computer engineering professionals and students

The evidence suggests that emotional intelligence and personality traits are important qualities that workers need in order to successfully exercise a profession. This article assumes that the main purpose of universities is to promote employment by providing an education that facilitates the acquisition of abilities, skills, competencies and values. In this study, the emotional intelligence and personality profiles of two groups of Spanish students studying degrees in two different academic disciplines – computer engineering and teacher training – were analysed and compared. In addition, the skills forming part of the emotional intelligence and personality traits required by professionals (computer engineers and teachers) in their work were studied, and the profiles obtained for the students were compared with those identified by the professionals in each field. Results revealed significant differences between the profiles of the two groups of students, with the teacher training students scoring higher on interpersonal skills; differences were also found between professionals and students for most competencies, with professionals in both fields demanding more competencies that those evidenced by graduates. The implications of these results for the incorporation of generic social, emotional and personal competencies into the university curriculum are discussed.

An experience on mechatronics teaching on undergraduate students by means of the Skybot platform: from classroom to robot competition

This paper analyzes the learning experiences and opinions from a group of undergraduate students in a course about Robotics. The contents of this course were taught as a set of seminars. In each seminar, the student learned interdisciplinary knowledge of computer science, control engineering, electronics and other fields related to Robotics. The aim of this course is that the students are able to design and implement their own and custom robotic solution for a series of tests planned by the teachers. These tests measure the behavior and mechatronic features of the students' robots. Finally, the students' robots are confronted with some competitions. In this paper, the low-cost robotic architecture used by the students, the contents of the course, the tests to compare the solutions of students and the opinion of them are amply discussed.

A combined probabilistic framework for learning gestures and actions

In this paper we introduce a probabilistic approach to support visual supervision and gesture recognition. Task knowledge is both of geometric and visual nature and it is encoded in parametric eigenspaces. Learning processes for compute modal subspaces (eigenspaces) are the core of tracking and recognition of gestures and tasks. We describe the overall architecture of the system and detail learning processes and gesture design. Finally we show experimental results of tracking and recognition in block-world like assembling tasks and in general human gestures.