Students will attain a historical view of sports technology and biomechanics. They will be able to use a range of biomechanical principles and apply these collaboratively and individually in a practical sporting context utilising video analysis software. Students will develop knowledge and skills on the application of a range of technology innovations that enhance and analyse sporting performance.
Analyse recent scientific literature relating to technology in sport and its impact on coaching practice. Particular emphasis will be placed on: (i)historical development, (ii) theoretical frameworks, (iii)methodological approaches and best practice (iv) issues relating to reliability and validity, and (v) key findings in sports performance analysis. Technical Skill AnalysisVideo analysis of an elite athlete performing a skill. Coding development. Develop an understanding based on the mechanical reasons each key element is performed in this manner. Video analysis of a non elite athletes skill execution. Application of video notational analysis to identify skill deficits, provide effective feedback and corrective practices to improve technical competence.Movement Skill AnalysisVideo analysis to identify phases and key performance indicators associated with elite sports performers movement mechanics. Aplpication of this best practice model to analyse non elite athletes movement using video analysis software. Development of corrective feedback and appopriate exercises to improve competence of movement.Sport physiological needs analysisUse of objective measures such as sports GPS tracking devices and acceleromters to assess and monitor physiological demands of sports e.g. distance, speed, acceleration, speed zones etc. Application of these findings based on the Theory of Specificity to inform physical fitness needs of sports.Technological Tools to Assist CoachesAnalysis of recently developed sport science technologies e.g. sports apps to monitor, assess and improve movement and sports performance e.g. Coaches eye, Kinesiocapture.
Methods used to achieve the module learning outcomes will include lectures, tutorials, laboratory practicals, interpretation of data, case studies, problem-solving exercises, video presentations, self-directed learning and computer-based learning.
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