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251.
Jorge E. Morais António J. Silva Nuno D. Garrido Daniel A. Marinho Tiago M. Barbosa 《European Journal of Sport Science》2018,18(6):787-795
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?.001), except the TV–SL and the TV–SF path. At M3, all links between variables presented significant effects (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. 相似文献
252.
Jorge Fernández Herrero Francisco Gómez Donoso Rosabel Roig Vila 《British journal of educational technology : journal of the Council for Educational Technology》2023,54(6):1939-1963
To test the suitability of an automatic system for emotional management in the classroom following the control-value theory of achievement emotions (CVT) framework, the performance of an emotional expression recognition software of our creation is evaluated in an online synchronous context. Sixty students from the Faculty of Education at the University of Alicante participated in 16 educational activities recording close-ups of their faces and completing the AEQ emotional self-report, as well as detailed reports from the subsequent review of their videos. In addition, they completed the VCQ-36 test to measure their volitional competencies and relate their influence on their emotional response. The results indicate a high coherence between the emotional expressions detected by the automatic system and the detailed emotional self-reports, but insufficient precision to meet the CVT requirements. On the other hand, both the AEQ test results and the emotion expression recognition software suggest students' preference for participative activities as opposed to passive ones. Meanwhile, statistical analysis results indicate that volitional competencies seem to influence the emotional response of students in the educational context, although the AI system does not show sufficient sensitivity in this field. Implications and limitations of this study for future work are discussed.
Practitioner notes
What is already known about this topic
- Student motivation and involvement in the learning process are highly related to appropriate emotional regulation, which can be associated with particular educational activities, strategies and methodologies.
- Deep learning technology based on convolutional neural networks feeds automatic systems focused on facial expression recognition from image analysis.
What this paper adds
- There is high coherence between the emotional expressions detected by the AI system and the students' emotional self-reports, but the AI system provides just emotional valences, insufficient to meet the CVT framework.
- Both emotional self-reports and the emotion recognition software suggest students' preference for active educational activities as opposed to passive ones.
- Volitional competencies seem to influence the emotional response of students in the educational context.
Implications for practice and/or policy
- It is possible to use automatic systems to effectively monitor the emotional response of students in the learning process.
- Only if sensitivity improved, a real-time, easy-to-interpret emotional expression recognition software interface could be implemented to assist teachers with the emotional management of their classes within the CVT framework, maximizing their motivation and engagement.