On the Validity of the Knowledge Transferring Assessment of the Knowledge‐Based System for Training Long Jump Athletes: The Approach‐Run Phase
Keywords:
knowledge-based system, knowledge engineering, knowledge transfer, approach-run, long jump biomechanics, computer vision, validityAbstract
Precise measurements of maximum speed and position of maximum speed during sprinting have essential inferences for planning and improving the individual performance of long jump athletes. Coaching in the approach-run phase is somewhat difficult because the athlete’s movement is very fast. Therefore, the aim of this study was to evaluate the validity of the knowledge transferring of Knowledge-Based System (KBS) for training long jumpers in the approach-run phase which was compared with the Tracker video analysis software. Twelve healthy adults (Average age=27.58 years old, SD=9.67, Variance=93.53) were randomly selected for data collecting. The participants performed walking, jogging, running and fast running trials and static starts at about 20-25 m. distance from a take-off board. Descriptive statistics, Cross-tabulation and Spearman's Rho were employed for statistical analysis. The results showed strong significant relationship between both systems at Spearman's Rho Correlation = 0.916, p-value <0.01. The results also indicated that the proposed KBS could be used to accurately evaluate transferring of knowledge in the approach-run phase.