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. The goal of this study is to understand users' cognitive capabilities and limitations in the context of parametric design so that more intuitive interfaces can be developed.
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 perceptual issue may lead to design failures. Novel interfaces are required to reduce if not eliminate these effects. To enhance designers' performance we propose using various techniques to visualize changes such as peripheral interface and visual dataflow programming.
Why Change Detection?
The causes of change detection issues (Even straightforward reasons are related to cognitive issues people experience - memory, comprehension, identification):
- Change magnitude is small.
- Zoom factor and model size.
- Occlusion. (Obstructed changes)
- Multiple locations. (Many changes occur at different locations of the model simultaneously.
- Chain of changes. (What effects what)
- Change blindness.