Improving bilingual higher education: Training university professors in content and language integrated learning

With increasing international mobility, higher education must cater to the varying linguistic and cultural needs of students. Successful delivery of courses through English as the vehicular language is essential to encourage international enrollment. However, this cannot be achieved without preparing university professors in the many intricacies delivering their subjects in English may pose. This paper aims to: share preliminary data concerning Content and Language Integrated Learning (CLIL) at Laureate Network Universities worldwide as few studies have been conducted at the tertiary level, reflect upon data regarding student and teacher satisfaction with CLIL at the Universidad Europea de Madrid (UEM), and to propose improvements in English-taught subjects.

Structural brain connectivity and cognitive ability differences: A multivariate distance matrix regression analysis

Neuroimaging research involves analyses of huge amounts of biological data that might or might not be related with cognition. This relationship is usually approached using univariate methods, and, therefore, correction methods are mandatory for reducing false positives. Nevertheless, the probability of false negatives is also increased. Multivariate frameworks have been proposed for helping to alleviate this balance. Here we apply multivariate distance matrix regression for the simultaneous analysis of biological and cognitive data, namely, structural connections among 82 brain regions and several latent factors estimating cognitive performance. We tested whether cognitive differences predict distances among individuals regarding their connectivity pattern. Beginning with 3,321 connections among regions, the 36 edges better predicted by the individuals' cognitive scores were selected. Cognitive scores were related to connectivity distances in both the full (3,321) and reduced (36) connectivity patterns. The selected edges connect regions distributed across the entire brain and the network defined by these edges supports high-order cognitive processes such as (a) (fluid) executive control, (b) (crystallized) recognition, learning, and language processing, and (c) visuospatial processing. This multivariate study suggests that one widespread, but limited number, of regions in the human brain, supports high-level cognitive ability differences. Hum Brain Mapp, 2016. © 2016 Wiley Periodicals, Inc.