In the Cognitive Science Lab, we study learning, visual attention, and their interconnections so that we can understand how learning changes the way we access information—both with our eyes, and via computer interfaces—and how accessing the correct information can improve our learning. Our methods are diverse: we use experimental studies, and naturalistic datasets of real world tasks (e.g., video games) in combination with eye-tracking, computational modelling of cognition, and big data analyses. 

Recent work incorporates custom human-computer interfaces and virtual reality into our toolbox. The new generation of spatial computing tools provided by virtual, mixed and augmented reality technologies both encourages and requires software design that respects how humans learn and attend. 

One project is aimed at designing and testing a new computer interface call Ex Novo, that is designed around what we know about human cognition.  The effectiveness of Human-Computer Interfaces (HCI) are constrained by the limits human memory and attention. From a human memory and attention standpoint, existing interfaces leave a lot to be desired.  The most common computer interface allows users to select actions from lists in a menu. The graphical user interface (GUI) minimizes memory costs, but requires visual inspection and careful targeting to select actions, thus slowing down performance.  In compensation, typical computer interfaces allow for rapid execution of actions via keyboard hotkeys (such as ctrl-c to copy). Some hotkey combinations are difficult to perform, requiring users to use awkward hand positions that require visual inspection of the keyboard to execute, and most hotkey combination are largely arbitrary, making memory of the cryptic combination a challenge. Another important problem is that these two ways of initiating actions (menus and hotkeys) are essentially entirely separate interfaces, and the time spent learning one does almost nothing to help with the other. 

Our Ex Novo  ( which means *from the beginning*) interface that unifies the speed of hotkeys with the learnability of a GUI.  Because it is a single consistent interface, users improve with experience from the slow visually-guided choices of the novice, to the rapid, automatic actions of an expert.  Our research investigates how speed and performance differs between ExNovo and traditional menu-based interfaces, and how interface elements such as sound and visual coding might help to make interfaces easier to learn. 

Another current project investigates learning and attention in virtual reality. VR has different costs and affordances, and our previous research suggests that learning and attention will be affected. This project first seeks to understand how will previous research applies to VR. 

Ongoing projects include a longitudinal study of  learning and information access of players of the online strategy game StarCraft 2.