Ko Watanabe
Andreas Dengel
Shoya Ishimaru
ABSTRACT
Engagement is one of the core cognitive states in communication. Increased engagement improves the quality and immersion of the conversation. In this demonstration, we aim to present a metacognition augmentation application called Metacognition-EnGauge. This work aims to discover three research questions. Does self-metacognition augmentation of engagement levels support participant to be engaged in the meetings? Does group-metacognition augmentation of engagement levels support participant to be engaged in the meetings? Do participants prefer none, self, or group-metacognition augmentation intervention in the online meetings? To answer these questions, we conducted online meeting experiments with 18 participants. As a result, we found that self-metacognition augmentation outperformed well on increasing average engagement levels. According to the survey, participant preference shows group-metacognition as the best intervention.
Supplemental Material
- Kenneth Holstein, Gena Hong, Mera Tegene, Bruce M. McLaren, and Vincent Aleven. 2018. The classroom as a dashboard: co-designing wearable cognitive augmentation for K-12 teachers. In Proceedings of the 8th International Conference on Learning Analytics and Knowledge (Sydney, New South Wales, Australia) (LAK ’18). Association for Computing Machinery, New York, NY, USA, 79–88. https://doi.org/10.1145/3170358.3170377Google Scholar
Digital Library
- Mikko Kytö, Ilyena Hirskyj-Douglas, and David McGookin. 2021. From Strangers to Friends: Augmenting Face-to-face Interactions with Faceted Digital Self-Presentations. In Proceedings of the Augmented Humans International Conference 2021 (Rovaniemi, Finland) (AHs ’21). Association for Computing Machinery, New York, NY, USA, 192–203. https://doi.org/10.1145/3458709.3458954Google ScholarDigital Library
- Masayasu Niwa, Katsutoshi Masai, Shigeo Yoshida, and Maki Sugimoto. 2023. Investigating Effects of Facial Self-Similarity Levels on the Impression of Virtual Agents in Serious/Non-Serious Contexts. In Proceedings of the Augmented Humans International Conference 2023 (Glasgow, United Kingdom) (AHs ’23). Association for Computing Machinery, New York, NY, USA, 221–230. https://doi.org/10.1145/3582700.3582721Google ScholarDigital Library
- Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, and Liang-Chieh Chen. 2018. Mobilenetv2: Inverted residuals and linear bottlenecks. In Proceedings of the IEEE conference on computer vision and pattern recognition. 4510–4520.Google ScholarCross Ref
- Soohyun Shin, Jaekyung Cho, and Seong-Woo Kim. 2021. Jumple: Interactive Contents for the Virtual Physical Education Classroom in the Pandemic Era. In Proceedings of the Augmented Humans International Conference 2021 (Rovaniemi, Finland) (AHs ’21). Association for Computing Machinery, New York, NY, USA, 268–270. https://doi.org/10.1145/3458709.3458964Google ScholarDigital Library
- Ko Watanabe, Tanuja Sathyanarayana, Andreas Dengel, and Shoya Ishimaru. 2023. EnGauge: Engagement Gauge of Meeting Participants Estimated by Facial Expression and Deep Neural Network. IEEE Access (2023).Google Scholar
- Ko Watanabe, Yusuke Soneda, Yuki Matsuda, Yugo Nakamura, Yutaka Arakawa, Andreas Dengel, and Shoya Ishimaru. 2021. Discaas: Micro behavior analysis on discussion by camera as a sensor. Sensors 21, 17 (2021), 5719.Google ScholarCross Ref
Index Terms
- Metacognition-EnGauge: Real-time Augmentation of Self-and-Group Engagement Levels Understanding by Gauge Interface in Online Meetings
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