Influence of Individual Differences when Training Public Speaking with Virtual Audiences

Mathieu Chollet (1) , Pranav Ghate (1) , Catherine Neubauer (1) , Stefan Scherer (1)

1 ICT - Institute for Creative Technologies

Multimodal interaction technologies have enabled new applications for training interpersonal skills such as public speaking. Various training paradigms have been proposed, most of them relying on some form of graphical feedback provided to the trainee in real-time during their training or after training using an after-action review tool. Another paradigm consists of using virtual characters to provide feedback through their behavior during simulated social interactions. Preliminary studies have started to explore the effectiveness of these different training paradigms; however, these have not investigated the impact of individual differences on which interaction paradigm is more efficient or motivating for different populations of users. In this article, we explore the impact of personality, public speaking anxiety, and immersive tendencies on the experiences of users training public speaking with an interactive virtual audience system providing realtime feedback through virtual audience behavior as well as delayed feedback with an after-action review tool. We found that these three factors impacted different output measures of user experience and user ratings of the system's quality.

Domaines: Environnements Informatiques pour l'Apprentissage Humain; Intelligence artificielle [cs.AI]; Interface homme-machine [cs.HC]; Apprentissage [cs.LG]

Mathieu Chollet, Pranav Ghate, Catherine Neubauer, Stefan Scherer. Influence of Individual Differences when Training Public Speaking with Virtual Audiences. Intelligent Virtual Agents, Nov 2018, Sydney, Australia. pp.1-7, ⟨10.1145/3267851.3267874⟩. ⟨hal-02439036⟩