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Automotive user interfaces and, in particular, automated vehicle technology pose a plenty of challenges to researchers, vehicle manufacturers, and third-party suppliers to support all diverse facets of user needs. To give an example, they emerge from the variation of different user groups ranging from inexperienced, thrill-seeking young novice drivers to elderly drivers with all their natural limitations. To allow assessing the quality of automotive user interfaces and automated driving technology already during development and within virtual test processes, the proposed workshop is dedicated to the quest of finding objective, quantifiable quality criteria for describing future driving experiences. The workshop is intended for HCI, AutomotiveUI, and "Human Factors" researchers and practitioners as well for designers and developers. In adherence to the conference main topic "Spielend einfach interagieren" this workshop calls in particular for contributions in the area of human factors and ergonomics (user acceptance, trust, user experience, driving fun, natural user interfaces etc.) and artificial intelligence (predictive HMIs, adaptive systems, intuitive interaction).
Group-centered framework towards a positive design of digital collaboration in global settings
(2017)
Globally distributed groups require collaborative systems to support their work. Besides being able to support the teamwork, these systems also should promote well-being and maximize the human potential that leads to an engaging system and joyful experience. Designing such system is a significant challenge and requires a thorough understanding of group work. We used the field theory as a lens to view the essential aspects of group motivation and then utilized collaboration personas to analyze the elements of group work. We integrated well-being determinants as engagement factors to develop a group-centered framework for digital collaboration in a global setting. Based on the outcomes, we proposed a conceptual framework to design an engaging collaborative system and recommend system values that can be used to evaluate the system further.