The transfer of strength and power into the stroke biomechanics of young swimmers over a 34-week period

The purpose of this study was to learn the interplay between dry-land strength and conditioning, and stroke biomechanics in young swimmers, during a 34-week training programme. Twenty-seven swimmers (overall: 13.33?±?0.85 years old; 11 boys: 13.5?±?0.75 years old; 16 girls: 13.2?±?0.92 years old) competing at regional- and national-level competitions were evaluated. The swimmers were submitted to a specific in-water and dry-land strength training over 34 weeks (and evaluated at three time points: pre-, mid-, and post-test; M1, M2, and M3, respectively). The 100-m freestyle performance was chosen as the main outcome (i.e. dependent variable). The arm span (AS; anthropometrics), throwing velocity (TV; strength), stroke length (SL), and stroke frequency (SF; kinematics) were selected as independent variables. There was a performance enhancement over time (M1 vs. M3: 68.72?±?5.57?s, 66.23?±?5.23?s; Δ?=??3.77%; 95% CI: ?3.98;?3.56) and an overall improvement of the remaining variables. At M1 and M2, all links between variables presented significant effects (p?p?≤?.05). Between M1 and M3, the direct effect of the TV to the stroke biomechanics parameters (SL and SF) increased. The model predicted 89%, 88%, and 92% of the performance at M1, M2, and M3, respectively, with a reasonable adjustment (i.e. goodness-of-fit M1: χ²/df?=?3.82; M2: χ²/df?=?3.08; M3: χ²/df?=?4.94). These findings show that strength and conditioning parameters have a direct effect on the stroke biomechanics, and the latter one on the swimming performance.     

Learning through chemistry simulations: an analysis of cognitive skill levels

Education and Information Technologies - This paper presents an analysis of cognitive skill levels expressed in high school students’ performance using laboratory simulations. We address...     

University entrepreneurial performance: A Fuzzy Set Qualitative Comparative Analysis

As key players in innovation and entrepreneurial ecosystems, Higher Education Institutions (HEI) assume a position as catalysts in creating and disseminating knowledge with repercussions in the societal, economic, political and innovation environments. In this scenario, HEI are facing the need to balance the performance of their traditional missions—teaching and research—with the pursuit of entrepreneurial performance. This brings awareness of the need to pay particular attention to HEI entrepreneurial performance (HEIEP) and how to measure it. Based on HEInnovate, a self-assessment tool resulting from a joint effort of the European Community and the OECD, this study aims to explore the benefits of university entrepreneurial metrics, analysing HEIEP as a discriminant function of the HEInnovate dimensions complemented with a qualitative approach using Fuzzy Set Qualitative Comparative Analysis (fsQCA). The analysis provides valuable details, presenting recipes based on the HEInnovate dimensions or combinations of dimensions to achieve a mission legitimation. This research brings awareness to the use of the HEInnovate scale, where it is possible to highlight the importance of the digital transformation and capability dimension to entrepreneurial performance (EP) and university mission legitimation.     

Grade retention and school entry age in Spain: a structural problem

Educational Assessment, Evaluation and Accountability - Grade retention has been the focus of the education debate in Spain for decades. On average, more than 30% of students have repeated at least...