The Impact of Different Virtual Work Environments on Flow, Performance, User Emotions, and Preferences
Alicja Kiluk, Viktorija Paneva, Sofia Seinfeld, Jörg Müller
备注:
6 pages, 8 figures. This is the author's version. Final version of records is to appear in 2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)
This research explores how different virtual work environments, differing in the type and amount of elements they include, impact users' flow, performance, emotional state, and preferences. Pre-study interviews were conducted to inform the design of three VR work environments: the Dark Room, the Empty Room, and the Furnished Room. Fifteen participants took part in a user study where they engaged in a logic-based task simulating deep work while experiencing each environment. The findings suggest that while objective performance measures did not differ significantly, subjective experiences and perceptions varied across the environments. Participants reported feeling less distracted and more focused in the Dark Room and the Empty Room compared to the Furnished Room. The Empty Room was associated with the highest levels of relaxation and calmness, while the Furnished Room was perceived as visually appealing yet more distracting. These findings highlight the variability of user preferences and emphasise the importance of considering user comfort and well-being in the design of virtual work environments. The study contributes to the better understanding of virtual workspaces and provides insights for designing environments that promote flow, productivity, and user well-being.
EmoPrefer: Can Large Language Models Understand Human Emotion Preferences?
Institute of Automation, Chinese Academy of Sciences(中国科学院自动化研究所);University of Oulu(奥卢大学);Shenzhen University(深圳大学);Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ)(广东省人工智能与数字经济实验室(深圳));The Chinese University of Hong Kong(香港中文大学);Shanghai Jiaotong University(上海交通大学);Shenzhen Technology University(深圳理工大学);Department of Automation, BNRist, Tsinghua University(清华大学自动化系、北京信息科学与技术国家研究中心)
Learning to Prefer Reliably: Error-Augmented Emotion Preference Optimization with Calibrated Fusion
Hong Kong Polytechnic University(香港理工大学);Brno University of Technology(布尔诺理工大学);Tsinghua University(清华大学);National Taiwan University(台湾大学);Kyoto University(京都大学)
Emotional Storytelling using Virtual and Robotic Agents
University of Minho(米尼奥大学);Universidad Politecnica de Madrid(马德里理工大学);Hongik University(弘益大学);Interactive Robots and Media Lab (IRML)(交互机器人与媒体实验室(IRML))
Revealing Preference in Popular Music Through Familiarity and Brain Response
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Exploring Emotion Expression Recognition in Older Adults Interacting with a Virtual Coach
Universitat de Barcelona(巴塞罗那大学);Computer Vision Center(计算机视觉中心);Universidad del País Vasco UPV-EHU(巴斯克大学);SAMOVAR;Telecom SudParis(巴黎高等电信学院);Institut Polytechnique de Paris(巴黎综合理工学院);Università degli Studi della Campania L. Vanvitelli(坎帕尼亚大学);Universidad Internacional de La Rioja(拉里奥哈国际大学);Osatek;Oslo University Hospital(奥斯陆大学医院)
I Probe, Therefore I Am: Designing a Virtual Journalist with Human Emotions
University of California, Santa Cruz(加州大学圣克鲁兹分校);University of Nottingham(诺丁汉大学);The National Institute of Mental Health(国家心理健康研究所);Istanbul Technical University(伊斯坦布尔理工大学);University of Twente(特文特大学)