Abstract
In recent years, there has been an increased interest in the role of social agents as language teachers. Our experiment was designed to investigate whether a physical agent in form of a social robot provides a better language-learning experience than a virtual agent. We evaluated the interactions regarding enjoyment, immersion, and vocabulary retention. The 55 participants who took part in our study learned 5 phrases of the fictional language High Valyrian from the TV show Game of Thrones. For the evaluation, questions from the Almere model, the Godspeed questionnaire and the User Engagement Scale were used as well as a number of custom questions. Our findings include statistically significant results regarding enjoyment (\(p=0.008\)) and immersion (\(p=0.023\)) for participants with little or no prior experience with social robots. In addition, we found that the participants were able to retain the High Valyrian phrases equally well for both conditions.
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- 1.
https://www.duolingo.com/courses (accessed 21/08/2019).
- 2.
https://godotengine.org/ (accessed 21/08/2019).
- 3.
A popular character from Game of Thrones speaking High Valyrian.
- 4.
http://wiki.ros.org/smach (accessed 21/08/2019).
- 5.
http://www.ros.org/ (accessed 21/08/2019).
- 6.
https://aws.amazon.com/polly/ (accessed 21/08/2019).
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Ali, H. et al. (2019). Virtual or Physical? Social Robots Teaching a Fictional Language Through a Role-Playing Game Inspired by Game of Thrones. In: Salichs, M., et al. Social Robotics. ICSR 2019. Lecture Notes in Computer Science(), vol 11876. Springer, Cham. https://doi.org/10.1007/978-3-030-35888-4_33
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