Acquisition of embodied skills in sports can be regarded as a process in which an athlete explores how to move his or her own body. It is important for an athlete to explore his or her own body movements in order to construct an internal skill model. Meta-cognitive verbalization about one's own body movements is one of the methods for accelerating the exploration process. The literature indicates that meta-cognitive verbalization is effective for acquisition of embodied skills, and suggests that such support based on motion measurement that encourages this verbalization is necessary. This study explores ways to encourage meta-cognitive verbalization based on motion data. This paper presents a software tool to simply represent and visualize changes of an athlete's body posture. The software segments an athlete's body movements into discrete phases according to similarity, and represents each phase by one color. The procedure consists of motion measurement by using an optical motion-capture system, segmentation of body movements by a K-means algorithm, and visualization by color. The visualization of body movements by color gives an athlete an opportunity for meta-cognitive exploration. In the case study of baseball swing practice, using the visualization software helped a baseball player discover an important aspect of his form and facilitated a remarkable improvement of his batting average.
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