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Journal of Computer Assisted Learning
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Journal of Computer Assisted Learning
Article . 2017 . Peer-reviewed
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Presentation Trainer: what experts and computers can tell about your nonverbal communication

what experts and computers can tell about your nonverbal communication
Authors: Jan Schneider 0001; Dirk Börner; Peter van Rosmalen; Marcus Specht;

Presentation Trainer: what experts and computers can tell about your nonverbal communication

Abstract

AbstractThe ability to present effectively is essential for professionals; therefore, oral communication courses have become part of the curricula for higher education studies. However, speaking in public is still a challenge for many graduates. To tackle this problem, driven by the recent advances in computer vision techniques and prosody analysis, multimodal tools have been designed to support the development of public speaking skills. One of these tools is thePresentation Trainer, a research prototype able to provide learners with real‐time feedback on a set of nonverbal communication aspects. Despite initial positive evaluations, the application still lacks grounding in a valid assessment model for nonverbal communication aspects in the context of presentations. To come up with such a model, we conducted semi‐structured interviews with experts in the public speaking domain. Furthermore, the objective of these interviews was also to have a formative evaluation of thePresentation Trainer, analysing how it suits with common practices for teaching and learning public speaking skills. The results of this study identify 131 nonverbal communication practices that affect the quality of a presentation and summarize experts' points of view regarding multimodal public speaker instructors.

Country
Netherlands
Related Organizations
Keywords

expert study, public speaking, nonverbal communication, multimodal systems, sensor-based learning.

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    25
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
25
Top 10%
Top 10%
Top 10%
Green
hybrid