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Gestalt Laws in User Experience Design: A NeuroIS Research Agenda

In: Information Systems and Neuroscience

Author

Listed:
  • Anita Vogl

    (University of Applied Sciences Upper Austria, Digital Business Institute, School of Business and Management)

  • René Riedl

    (University of Applied Sciences Upper Austria, Digital Business Institute, School of Business and Management
    Johannes Kepler University Linz, Institute of Business Informatics—Information Engineering)

Abstract

Gestalt laws were described more than 100 years ago. Gestalt laws are psychological principles that describe how humans naturally perceive and organize visual elements into unified wholes based on patterns, proximity, similarity, continuity, closure, connectedness, and some other factors. With the invention of graphical user interfaces, Gestalt laws became an essential part of user interface design. While user interfaces have changed and become more ubiquitous, weaving themselves into our everyday environment, the motivation to make user interfaces enjoyable is as important as ever. Previous empirical research has focused on self-report measures (mainly surveys and interviews) and has hardly used neurophysiological measures. However, since the perceptual qualities underlying Gestalt laws are strongly related to unconscious and emotional processes in the human nervous system, it is essential that future research also uses neurophysiological tools. In essence, such an increased use of neurophysiological data allows for a more informed investigation of the influences of Gestalt laws on usability and user experience (UX), leading to the design of more pleasurable and enjoyable user interfaces. In this paper, we present a research agenda that integrates the fields of UX design based on Gestalt laws and NeuroIS.

Suggested Citation

  • Anita Vogl & René Riedl, 2025. "Gestalt Laws in User Experience Design: A NeuroIS Research Agenda," Lecture Notes in Information Systems and Organization, in: Fred D. Davis & René Riedl & Jan vom Brocke & Pierre-Majorique Léger & Adriane B. Randolph & Gernot (ed.), Information Systems and Neuroscience, pages 233-242, Springer.
    • Handle: RePEc:spr:lnichp:978-3-032-00815-2_22
    DOI: 10.1007/978-3-032-00815-2_22
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