The Effects of a Self-Similar Avatar Voice in Educational Games

Avatar identification is one of the most promising research areas in games user research. Greater identification with one's avatar has been associated with improved outcomes in the domains of health, entertainment, and education. However, existing studies have focused almost exclusively on the visual appearance of avatars. Yet audio is known to influence immersion/presence, performance, and physiological responses. We perform one of the first studies to date on avatar self-similar audio. We conducted a 2 x 3 (similar/dissimilar x modulation upwards/downwards/none) study in a Java programming game. We find that voice similarity leads to a significant increase in performance, time spent, similarity identification, competence, relatedness, and immersion. Similarity identification acts as a significant mediator variable between voice similarity and all measured outcomes. Our study demonstrates the importance of avatar audio and has implications for avatar design more generally across digital applications.