P
Paweł W. Woźniak
Researcher at Utrecht University
Publications - 113
Citations - 1268
Paweł W. Woźniak is an academic researcher from Utrecht University. The author has contributed to research in topics: Computer science & User experience design. The author has an hindex of 14, co-authored 91 publications receiving 684 citations. Previous affiliations of Paweł W. Woźniak include University of Stuttgart & Chalmers University of Technology.
Papers
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Proceedings ArticleDOI
Supporting Meaningful Personal Fitness: the Tracker Goal Evolution Model
Jasmin Niess,Paweł W. Woźniak +1 more
TL;DR: The model describes how tracker goals can evolve from internal user needs through qualitative goals to quantitative goals that can be used with trackers and is useful for designers of future trackers to create evolving and meaningful tracking goals.
Proceedings ArticleDOI
Reading on Smart Glasses: The Effect of Text Position, Presentation Type and Walking
TL;DR: A study with 24 participants using a Microsoft HoloLens to investigate how to display text on smart glasses while walking and sitting found that text displayed in the top-right of smart glasses increases subjective workload and reduces comprehension.
Proceedings ArticleDOI
RUFUS: Remote Supporter Feedback for Long-Distance Runners
TL;DR: This paper explores remote cheering during amateur races through a formative design inquiry and finds that two-way communication between runners and supporters was achieved and that the system reflected varying user needs correctly.
Journal ArticleDOI
Technologies for Enhancing Collocated Social Interaction: Review of Design Solutions and Approaches
Thomas Olsson,Pradthana Jarusriboonchai,Paweł W. Woźniak,Susanna Paasovaara,Kaisa Väänänen,Andrés Lucero +5 more
TL;DR: This literature review outlines the landscape of design explorations in this emergent research topic and identifies various roles of technology relevant for enhancement, representing three abstract categories: facilitating, inviting and encouraging.
Proceedings ArticleDOI
Your Eyes Tell: Leveraging Smooth Pursuit for Assessing Cognitive Workload
TL;DR: This work compares three trajectories and two speeds under different levels of cognitive workload within a user study and finds higher deviations of gaze points during smooth pursuit eye movements for specific trajectory types at higher cognitive workload levels.