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Auflistung nach Schlagwort "Human factors"

1 - 4 von 4
  • Konferenzbeitrag
    Code Comprehension Confounders: A Study of Intelligence and Personality
    (Software Engineering 2024 (SE 2024), 2024) Stefan Wagner; Marvin Wyrich
  • Zeitschriftenartikel
    Empirical Evidence for Context-aware Interfaces to Pedestrian Navigation Systems
    (KI - Künstliche Intelligenz: Vol. 28, No. 4, 2014) Ludwig, Bernd; Müller, Manuel; Ohm, Christina
    For geographical mobile search tasks it is rarely sufficient to assist users identifying what location they are currently looking for, e.g. a store, cafe or museum. Often the user needs support in being guided to a retrieved location in a physical space. This means that mobile search is strongly connected with navigation. There is a large body of work indicating that navigating towards points of interest is challenging for many people. In this work we explore how to support best this part of the task by investigating how objects in the physical world—landmarks—can be used in information systems to guide people to their desired location. We present the results of a series of eye tracking studies on the orientation behavior of persons executing indoor navigation tasks. The main finding of the studies is that the contextual relevance and the function of a landmark for completing the task efficiently matters more than the context-free salience of the same landmark. The findings have implications for the design of mobile search systems that support geographical search tasks as they lead to new context-adaptive strategies for navigation systems to explain routes. We provide evidence that even the interface has to adapt its content on the state of the navigation task and the current spatial context in order to provide user- and context-adaptive intuitive interaction.
  • Konferenzbeitrag
    Modeling User Interaction at the Convergence of Filtering Mechanisms, Recommender Algorithms and Advisory Components
    (Mensch und Computer 2021 - Tagungsband, 2021) Kleemann, Timm; Wagner, Magdalena; Loepp, Benedikt; Ziegler, Jürgen
    A variety of methods is used nowadays to reduce the complexity of product search on e-commerce platforms, allowing users, for example, to specify exactly the features a product should have, but also, just to follow the recommendations automatically generated by the system. While such decision aids are popular with system providers, research to date has mostly focused on individual methods rather than their combination. To close this gap, we propose to support users in choosing the right method for the current situation. As a first step, we report in this paper a user study with a fictitious online shop in which users were able to flexibly use filter mechanisms, rely on recommendations, or follow the guidance of a dialog-based product advisor. We show that from the analysis of the interaction behavior, a model can be derived that allows predicting which of these decision aids is most useful depending on the user’s situation, and how this is affected by demographics and personality.
  • Workshopbeitrag
    On the Convergence of Intelligent Decision Aids
    (Mensch und Computer 2021 - Workshopband, 2021) Loepp, Benedikt
    On the one hand, users’ decisionmaking in today’sweb is supported in numerous ways, with mechanisms ranging from manual search over automated recommendation to intelligent advisors. The focus on algorithmic accuracy, however, is questioned more and more. On the other hand, although the boundaries between the mechanisms are blurred increasingly, research on user-related aspects is still conducted separately in each area. In this position paper, we present a research agenda for providing a more holistic solution, in which users are supported with the right decision aid at the right time depending on personal characteristics and situational needs.