A Preliminary Study of Using Laban Movement Analysis to Observe The Change of Teenagers' Bodily Expressions of Emotions in Game-based Learning

This study aims to develop a recognition system of bodily expressions of emotions (BEE) that can be applied to digital kinetic games. There were three stages of the study. First, 76 emotion and action terms frequently used by teenagers were selected; they were quantized into four quadrants, and gathered into 16 clusters. The second stage is to construct the database of emotional motions. The researchers collected the data of body motions expressed in accordance to the 16 emotion terms, classified the attributions of body motions using the particular factors of Effort and Space Harmony based on Laban Movement Analysis (LMA). The last stage is to construct the algorithms of BEE based on the attribution database built in the earlier stage. Finally, the researchers would compare the results of the digital recognition system with the database that was built in the second stage to secure the accuracy of the recognition system. Once the body recognition system was built, it would be an important research tool and mechanism to recognize the emotional changes of the player during the kinetic game play, and compare the learning conditions with learning effectiveness to do further investigations.