<![CDATA[Footwork is a crucial component of table tennis athletes’ performance; however, its measurement and training are still conducted manually, making them less efficient and less objective. This study aims to develop a footwork instrument based on the Internet of Things (IoT) using the Ryu Seung Mon approach to improve the accuracy, effectiveness, and efficiency of training. The research employed a Research and Development (R&D) method using the Borg & Gall development model, which was simplified into several stages: identifying potential and problems, data collection, product design, design validation, revision, and limited trials. The small-group trial involved 25 participants, while the large-group trial involved 40 participants. The results indicate that the IoT-based footwork instrument is capable of recording athletes’ movements in real time, providing immediate feedback, and analyzing movement speed and accuracy based on the Ryu Seung Mon footwork pattern. Validation results showed that the first material expert rated the product at 86.33%, the second material expert at 88.75%, the first media expert at 91.66%, the second media expert at 90.25%, and the technology expert also indicated that the product is feasible for use in table tennis training. The significance of these findings demonstrates that the integration of IoT in sports training can quantitatively and objectively enhance the quality of coaching. In conclusion, this instrument is effective as a footwork measurement tool and represents a technological innovation in improving table tennis athletes’ performance. The primary limitation of this study lies in the potential low external validity and long-term reliability of the instrument due to its dependence on the stability of IoT devices.]]>
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