The effect of motion in graphical user interfaces

Paul U. Lee, Alexander Klippel, Heike Tappe

Research output: Chapter in Book/Report/Conference proceedingChapter

14 Scopus citations

Abstract

Motion can be an effective tool to focus user's attention and to support the parsing of complex information in graphical user interfaces. Despite the ubiquitous use of motion in animated displays, its effectiveness has been marginal at best. The ineffectiveness of many animated displays may be due to a mismatch between the attributes of motion and the nature of the task at hand. To test this hypothesis, we examined different modes of route presentation that are commonly used today (e.g. internet maps, GPS maps, etc.) and their effects on the subsequent route memory. Participants learned a route from a map of a fictitious town. The route was presented to them either as a solid line (static) or as a moving dot (dynamic). In a subsequent memory task, participants recalled fewer pertinent landmarks (i.e. landmarks at the turns) in the dynamic condition, likely due to the moving dot that focused equally on critical and less important parts of the route. A second study included a combined (i.e. both static and dynamic) presentation mode, which potentially had a better recall than either presentation mode alone. Additionally, verbalization data confirmed that the static presentation mode allocated the attention to the task relevant information better than the dynamic mode. These findings support the hypothesis that animated tasks are conceived of as sequences of discrete steps, and that the motion in animated displays inhibits the discretization process. The results also suggest that a combined presentation mode can unite the benefits of both static and dynamic modes.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsAndreas Butz, Antonio Kruger, Patrick Olivier
PublisherSpringer Verlag
Pages12-21
Number of pages10
ISBN (Print)3540405577
DOIs
StatePublished - 2003

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2733
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this