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Auflistung nach Autor:in "Carolus, Astrid"

1 - 3 von 3
  • Konferenzbeitrag
    Adopting Just Another Digital Assistant or Establishing Social Interactions with a New Friend?
    (Mensch und Computer 2022 - Tagungsband, 2022) Carolus, Astrid; Wienrich, Carolin
    Social interactions have been exclusive to human-human interactions, until recently. However, modern technologies with adaptive and intelligent features such as smart speakers imitate human social characteristics and appear to be allegedly social interaction partners. Research going beyond the analysis of mere usage and conceptualizing devices as interaction partners is rare, also because studying the establishment of social interactions would require analyses over time. The present paper addresses this research desideratum and introduces a concept of a longitudinal study which involves the collection of different data types from different sources (online questionnaire, providers’ log files, interview) and interdisciplinary data analytical methods (social science, data science). Its cross-sectional and longitudinal research questions ask for the adoption and the usage of the usage of smart speakers, for the establishment of social interactions with the device. In sum, this study contributes to the research area by presenting a conceptual research model, which provides a framework for the systematic long-term analysis of both the adoption of technology over time as well as the establishment of potential social interactions.
  • Workshopbeitrag
    How close do you feel to your devices? Visual assessment of emotional relationships with digital devices
    (Mensch und Computer 2019 - Workshopband, 2019) Carolus, Astrid; Wienrich, Carolin
    With modern digital devices becoming more adaptive and more personalized, usage behavior has changed dramatically. Devices are no longer mere technological equipment but are discussed to be “social companions” [1]. However, measures, scales and instruments barely keep in step with both the new ways of usage and the resulting new perspective on the devices [2]. Thus, measurements focusing on social and relational aspects of modern media use are rare. This paper addresses the need to develop new methodological approaches. Further, as online assessment tools are increasingly popular but face design-related disadvantages (e.g., termination, uncertain quality of data) it argues for a high quality design process. Consequently, this paper focuses on a new online instrument (labeled POD 1.0: Positioning Others and Devices) which has been developed to assess the relationship between users and their devices [1]. However, the first version of this tool raised problems (e.g., user errors, dropout rate). By attributing these shortcomings to design and layout [6, 11], a heuristic expert analysis of problems was conducted following a user-centered-design process (UCD). Three low fidelity prototypes resulted and were evaluated with evaluations leading on to the final prototype: POD 2.0. Further, this POD 2.0 was evaluated. 44 participants engaged in a long-term user study. Compared to the original tool, results revealed an improvement of both effectivity and satisfaction of the instrument. In sum, the present study brings instruments to focus which assess social and relational characteristics of a long-term user-device interaction. Further, user-centered-design processes are adopted to modify and refine the POD 1.0 indicating a promising way to improve the goodness of online assessment tools.
  • Workshopbeitrag
    What the user’s voice tells us about UX - Analysing parameters of the voice as indicators of the User Experience of the usage of intelligent voice assistants
    (Mensch und Computer 2020 - Workshopband, 2020) Obremski, David; Wienrich, Carolin; Carolus, Astrid
    This paper investigates voice parameters as indicators of the user experience during their interaction with voice-based technology. Following the requirements of a non-intrusive measurement and an automatic analysis, a tool is developed, which automatically measures and analyses speech recordings of users during interactions with voice assistants. The tool distinguishes between user- and voice assistant speech and analyses mean amplitude and pitch of user's speech as parameters reflecting the user experience of users. A user study presents first steps of a validation of the first version and reveals limitations and requirements for further developments.