The Swiss Vocational Education and Training System: What Can Spain Learn from Switzerland?

Switzerland is famous for its vocational education and training (VET) system. This article describes Switzerland's success in integrating adolescents into the labour market, with emphasis on two aspects. First, dual-track VET, which combines learning at school and in host companies, is an attractive choice for adolescents. It prepares them for the labour market and for progression routes to higher education. Second, the firm's decision to train could be an example of the prisoner's dilemma, but Switzerland has managed to sidestep that issue and minimize concerns about poaching. Finally, we discuss what Spain could learn from the Swiss VET system

Testing the potential of a virtual reality neurorehabilitation system during performance of observation, imagery and imitation of motor actions recorded by wireless functional near-infrared spectroscopy (fNIRS)

Background Several neurorehabilitation strategies have been introduced over the last decade based on the so-called simulation hypothesis. This hypothesis states that a neural network located in primary and secondary motor areas is activated not only during overt motor execution, but also during observation or imagery of the same motor action. Based on this hypothesis, we investigated the combination of a virtual reality (VR) based neurorehabilitation system together with a wireless functional near infrared spectroscopy (fNIRS) instrument. This combination is particularly appealing from a rehabilitation perspective as it may allow minimally constrained monitoring during neurorehabilitative training. Methods fNIRS was applied over F3 of healthy subjects during task performance in a virtual reality (VR) environment: 1) 'unilateral' group (N = 15), contralateral recording during observation, motor imagery, observation & motor imagery, and imitation of a grasping task performed by a virtual limb (first-person perspective view) using the right hand; 2) 'bilateral' group (N = 8), bilateral recording during observation and imitation of the same task using the right and left hand alternately. Results In the unilateral group, significant within-condition oxy-hemoglobin concentration Δ[O2Hb] changes (mean ± SD μmol/l) were found for motor imagery (0.0868 ± 0.5201 μmol/l) and imitation (0.1715 ± 0.4567 μmol/l). In addition, the bilateral group showed a significant within-condition Δ[O2Hb] change for observation (0.0924 ± 0.3369 μmol/l) as well as between-conditions with lower Δ[O2Hb] amplitudes during observation compared to imitation, especially in the ipsilateral hemisphere (p < 0.001). Further, in the bilateral group, imitation using the non-dominant (left) hand resulted in larger Δ[O2Hb] changes in both the ipsi- and contralateral hemispheres as compared to using the dominant (right) hand. Conclusions This study shows that our combined VR-fNIRS based neurorehabilitation system can activate the action-observation system as described by the simulation hypothesis during performance of observation, motor imagery and imitation of hand actions elicited by a VR environment. Further, in accordance with previous studies, the findings of this study revealed that both inter-subject variability and handedness need to be taken into account when recording in untrained subjects. These findings are of relevance for demonstrating the potential of the VR-fNIRS instrument in neurofeedback applications

How to detect and reduce movement artifacts in near-infrared imaging using moving standard deviation and spline interpolation

Near-infrared imaging (NIRI) is a neuroimaging technique which enables us to non-invasively measure hemodynamic changes in the human brain. Since the technique is very sensitive, the movement of a subject can cause movement artifacts (MAs), which affect the signal quality and results to a high degree. No general method is yet available to reduce these MAs effectively. The aim was to develop a new MA reduction method. A method based on moving standard deviation and spline interpolationwas developed. It enables the semi-automatic detection and reduction of MAs in the data. It was validated using simulated and real NIRI signals. The results show that a significant reduction ofMAs and an increase in signal quality are achieved. The effectiveness and usability of themethod is demonstrated by the improved detection of evoked hemodynamic responses. The present method can not only be used in the postprocessing of NIRI signals but also for other kinds of data containing artifacts, for example ECG or EEG signals

The costs of recruiting apprentices: Evidence from German workplace-level data

In this article, we use workplace-level data to analyse the costs of filling an apprenticeship vacancy in Germany. We find that such recruitment costs amount on average to (Sic) 600 per hire (almost one month's pay of an apprentice or approximately 1-2 % of a workplace's training expenditures), but costs are heterogeneous across workplaces and vary strongly by training occupation. Our results suggest that a high degree of competition among training workplaces in the region is associated with an increase in recruitment costs. Furthermore, we find that workplaces with a works council or an investment-oriented training strategy incur higher recruitment costs. Our results are important in light of the increasing competition for talented school leavers induced by demographic change