Art der Publikation: Beitrag in Sammelwerk

EngageMeter: A System for Implicit Audience Engagement Sensing Using Electroencephalography

Autor(en):

Hassib, Mariam; Schneegass, Stefan; Eiglsperger, Philipp; Henze, Niels; Schmidt, Albrecht; ; Alt, Florian

Titel des Sammelbands:

Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI '17)

Seiten:

5114-5119

Verlag:

ACM

Ort(e):

New York, USA

Veröffentlichung:

2017

ISBN:

978-1-4503-4655-9

Digital Object Identifier (DOI):

doi:https://doi.org/10.1145/3025453.3025669

Zitation:

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Kurzfassung

Obtaining information about audience engagement in presentations is a valuable asset for presenters in many domains. Prior literature mostly utilized explicit methods of collecting feedback which induce distractions, add workload on audience and do not provide objective information to presenters. We present EngageMeter - a system that allows fine-grained information on audience engagement to be obtained implicitly from multiple brain-computer interfaces (BCI) and to be fed back to presenters for real time and post-hoc access. Through evaluation during an HCI conference (Naudience=11, Npresenters=3) we found that EngageMeter provides value to presenters (a) in real-time, since it allows reacting to current engagement scores by changing tone or adding pauses, and (b) in post-hoc, since presenters can adjust their slides and embed extra elements. We discuss how EngageMeter can be used in collocated and distributed audience sensing as well as how it can aid presenters in long term use.