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Original Articles

Exploring the influence of audience familiarity on speaker anxiety and performance in virtual reality and real-life presentation contexts

ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Pages 787-799 | Received 17 Dec 2021, Accepted 16 Feb 2023, Published online: 07 Mar 2023
 

ABSTRACT

Virtual reality (VR) offers immense freedom in the design of virtual instructional environments, but little guidance exists on how to capitalise on this freedom. This article reports on a study exploring how audience familiarity influences public speaking anxiety (PSA) and performance in a presentation speaking task in virtuo and in situ. Questionnaire instruments were used to gauge the PSA, motivation, focus, and self-confidence of 10 undergraduate students who each presented in four different audience conditions across VR and real life. Presentations were transcribed to identify features of performance, including utterance fluency, and speaking breadth and depth. Outcomes indicated that an audience of computer-generated agents resulted in less PSA than an audience of photorealistic people familiar to the speakers. Additionally, presenting to an audience of strangers in real life induced the most anxiety, but the performance features of articulation rate, disfluencies, and frequency of silent pauses were significantly improved in this condition. The main contribution of this study is to show that presentations directed at virtual audiences exhibit less fluent speech in non-native speakers than speeches to a real audience.

Acknowledgements

The authors would like to thank Hongji Li, Yu Fu, and Luhan Wang for their expertise in creating the virtual environment used in this study.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Ethics statement

This research was approved by the university’s ethics committee and followed all required procedures to ensure the safety and consent of the participants.

Notes

Additional information

Funding

This work was supported by Xi’an Jiaotong-Liverpool University grant number TDF 18/19-R17-115.

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