CAADFutures 2011
Change Detection in 3D Parametric Systems: Human-Centered Interfaces for Change Visualization
Abstract
In the current rapid development of parametric design tools the underlying computational-technology outpaces interface design. Interaction with
these tools is becoming cognitively more demanding – for example, designers must switch between different views, manipulate views to adjust
working context in relation to the model, select operations with complex parameters, and differentiate reference geometry from design geometry.
During these complex activities, design models change partially or completely. The change can be initiated by the designer or invoked by a script;
and subsequently propagated to the rest of the model through parametric dependencies. Although the change can be part of the design logic, the
results may not be always obvious to the designer. The complexity in the system interfaces and the design model itself exacerbates this effect.
Typically designers must detect the location of change, its source, its magnitude, and its propagation path in order to make informed choice in
design.
The goal of this study understand users' cognitive capabilities and limitations in the context of parametric design so that more natural interfaces
can be developed. By interfaces, we mean both ‘user interfaces’ that come as part of the system and ‘custom-interfaces’ that can be developed
and used by the designer for a particular purpose. We bring attention particularly to the importance of change control and detection in 3D
parametric design. The term change detection refers to the visual processes involved in noticing, identifying, and localizing a change in a given
visuospatial context. Failure to properly detect changes may easily lead to frustration with modeling in 3D parametric systems and decrease
designers’ productivity and motivation regardless of powerful features provided. Moreover, such perceiptual failure may lead to design failures.
Novel interfaces are required to reduce if not eliminate these effects. In this paper, we aim to make a first step in developing a set of heuristics that
will present how designers’ change control and detection can be improved. We focus on user interfaces controlling and visualizing changes taking
place in the model on three different compositions in relation to the designer’s locus of attention. Our experimental study compared three types of
interfaces having: on model visualization, on periphery visualization and combined views. The changes that should be observed or tracked depend
on the design model at hand. Some examples of the changes are vector field direction, length or area, number of elements in the structure, and
sensitivity to input values. The interfaces in the study not exhaust these changes, but rather question what composition of interface would best
enable improved change detection and control. The first research goal is to understand if change ‘blindness’ significantly influences designers’
performance, and if so, how does location of visualization features (on model view, on peripheral view, and on combined view) influence designers’
change detection and localization. The study design measured the proportion of participants detecting a particular change, number of trials and
time required to complete each task, as well as difficulty level as evaluated by participants.
An interesting finding shows that visualizations on the visual periphery can equally support change detection as on model visualizations, but it is
significantly easier and faster to detect changes when they are visualized in both views. Furthermore, the quantitative and well as the qualitative
results support our hypothesis that change blindness significantly slows down and overloads design thinking, and thus should not be ignored. These
findings can guide us to develop better interfaces in 3D parametric systems.
Keywords :
Change detection, change blindness, user-centered design, interface ergonomics, HCI, CAD, 3D parametric systems, visualization
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