Modeling How Menu Search Strategies Develop with Experience

People involved

Gilles BAILLY
Daniel DUARTE
Antti OULASVIRTA
Luis LEIVA

Abstract

To find an item in a menu, users can follow different visual search strategies,
such as scanning items one by one (serial search) or trying to remember where
the item was (recall search). However, building predictive models of search
behavior has turned out to be challenging, because these strategies evolve
with practice. To address this challenge, we study theory-inspired models
of visual search in linear menus and propose a novel arbitration mechanism
to coordinate the adoption of such visual search strategies. Given a menu
design and the user’s previous experience with it, our approach predicts when
different search strategies (serial, recall, random) will be adopted and which
menu item will be fixated next. Our results (1) describe empirical data
plausibly with psychologically valid and interpretable models, (2) provide
new insights about how search strategies evolve with practice, and (3) show
how to infer search strategy from eye tracking data. To sum up, the models
provide a foundation to better understand how users learn to scan linear
menus

Project description