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Abstract

Collaborative spatial problem solving is an important yet not thoroughly examined task. We report first results regarding the performance differences between individual and collaborative spatial problem solving on the example of searching a large scale space. Participants navigated through a virtual city environment seeing only the environment part visible from their current location from a bird’s eye view map perspective. They used a joystick for movement and saw their visible section displayed on an individual monitor. In case of collaborative search their partner was displayed only when located within the area of visibility. Participants searched randomly generated non-grid, street networks of different complexity as implemented by the number of intersections. They searched the same environments once alone and once together with a partner with the order of testing balanced between participants. Participants’ task was to search the entire area as quickly as possible just as firefighters searching a burning building for victims. At each intersection and in the middle of each street leg an invisible target location was placed and participants heard a sound when visiting them for the first time. We recorded missed target locations, overall trajectory length and search time per person until self-indicating whole coverage. Our results show a general increase in missed locations, trajectory length, and search time with the complexity of the environment. These increases differed due to individual and collaborative search. For complex, but not for simple environments individual participants navigated shorter distances, finished earlier, but also missed more target locations than when searching the same environments in collaboration. These results indicate that in complex environments collaborative search is less error prone than individual search, but takes longer. Such initial findings will constrain future theorizing about collaborative spatial problem solving.