Active versus passive acquisition of spatial knowledge while controlling a vehicle in a virtual urban space in drivers and non-drivers

Historically real world studies have indicated a spatial learning advantage for active explorers of environments over those whose experience is more passive; a common contrast is made between car drivers and passengers. An experiment was conducted to explore the dual hypotheses that active explorers learn more about the layout of a virtual environment than passive observers and that real world car drivers will learn more regardless of their experimental Active/Passive status. Consistent with earlier studies in VEs, there was no benefit from activity (controlling exploration/movement), arguably because input control competes with spatial information acquisition. However, the results showed that Drivers were more accurate than Non-Drivers at indicating the positions of target locations on a map, in both active and passive conditions and had better route scores than Non-Drivers in the passive condition. It is argued that driving experience may convey a spatial learning advantage over and above activity per se

Spatial demands of concurrent tasks can compromise spatial learning of a virtual environment: implications for active input control

While active explorers in a real-world environment typically remember more about its spatial layout than participants who passively observe that exploration, this does not reliably occur when the exploration takes place in a virtual environment (VE). We argue that this may be because an active explorer in a VE is effectively performing a secondary interfering concurrent task by virtue of having to operate a manual input device to control their virtual displacements. Six groups of participants explored a virtual room containing six distributed objects, either actively or passively while performing concurrent tasks that were simple (such as card turning) or that made more complex cognitive and motoric demands comparable with those typically imposed by input device control. Tested for their memory for virtual object locations, passive controls (with no concurrent task) demonstrated the best spatial learning, arithmetically (but not significantly) better than the active group. Passive groups given complex concurrent tasks performed as poorly as the active group. A concurrent articulatory suppression task reduced memory for object names but not spatial location memory. It was concluded that spatial demands imposed by input device control should be minimized when training or testing spatial memory in VEs, and should be recognized as competing for cognitive capacity in spatial working memory

Drawing maps and remembering landmarks after driving in a virtual small town environment

Participants were designated active drivers or passive passengers according to whether or not they had control over the displacements of a virtual vehicle, while taking 5, 10 or 15 tours of a virtual small town environment. When tested later, passive passengers were able to remember more landmarks than the active drivers. However, with successive tours, participants in both groups were able to draw better survey maps of the environment, though this effect was greater in passive passengers. Landmark memory and map drawing ability were positively correlated. The results support models of spatial cognition that emphasise survey representations as the end product of spatial learning in new environments, but also emphasise that the acquisition of landmark information is continuous throughout this process

Spatial reconstruction following virtual exploration in children aged 5–9 years: effects of age, gender and activity–passivity

Children of 6–7, 7–8, and 8–9 years explored a virtual environment (VE) consisting of eight buildings distributed in a square arena marked off into four quadrants, as employed in an earlier real-space study. The children twice experienced a virtual space model, actively exploring (operating an input device), passively observing (watching the displacements made by an active participant), or viewing from eight static, pre-set perimeter viewpoints. They then used cardboard models to reconstruct the environment. Consistent with the earlier real-space study, performance (judged from placement distance errors) improved with age and with learning across two successive trials. Also consistent was that no difference was obtained between males and females, despite this having been expected in the VE version of the task. However, dissimilarity from the earlier study was that participants in the active exploration condition showed no advantage over those who viewed the environment from the perimeter. Moreover, those who passively observed the displacements made by an active participant actually demonstrated significantly superior spatial learning. Reasons for the absence of any active advantage, and the presence of a passive advantage, were discussed

Active and passive spatial learning from a desk-top virtual environment in male and female participants: a comparison with guessing controls

Undergraduate students were asked to explore a single room virtual environment (VE) containing 6 objects at floor level, depicted on a desk-top monitor. Exploration was either active (using keyboard keys to control displacements) or passive (observing an active participant), with male-male or female-female active-passive pairings. Following exploration, all participants were asked to independently complete a map task, requiring them to indicate the positions of 5 of the floor objects using a map which showed the one remaining (reference) object. Guessing controls performed the same task but without experience of the room or VE. No gender differences were obtained. Both active and passive exploration groups were more accurate than guessing controls, and no significant difference was obtained between the two exploration groups. The results are in agreement with several previous studies, which found no active-passive differences in VEs. This finding contrasts with real world exploration, where active-passive differences are invariably found. This difference might be explained if VE learning is more explicit than real-world learning, or if a VE imposes greater working memory load

Interface familiarity restores active advantage in a virtual exploration and reconstruction task in children.

Active exploration is reportedly better than passive observation of spatial displacements in real environments, for the acquisition of relational spatial information, especially by children. However, a previous study using a virtual environment (VE) showed that children in a passive observation condition performed better than actives when asked to reconstruct in reality the environment explored virtually. Active children were unpractised in using the input device, which may have detracted from any active advantage, since input device operation may be regarded as a concurrent task, increasing cognitive load and spatial working memory demands. To examine this possibility, 7-8-year-old children in the present study were given 5 minutes of training with the joystick input device. When compared with passive participants for spatial learning, active participants gave a better performance than passives, placing objects significantly more accurately. The importance of interface training when using VEs for assessment and training was discussed

Route learning and shortcut performance in adults with intellectual disability: a study with virtual environments

The ability to learn routes though a virtual environment (VE) and to make a novel shortcut between two locations was assessed in 18 adults with intellectual disability and 18 adults without intellectual disability matched on chronological age. Participants explored two routes (A ⇔ B and A ⇔ C) until they reached a learning criterion. Then, they were placed at B and were asked to find the shortest way to C (B ⇔ C, five trials). Participants in both groups could learn the routes, but most of the participants with intellectual disability could not find the shortest route between B and C. However, the results also revealed important individual differences within the intellectual disability group, with some participants exhibiting more efficient wayfinding behaviour than others. Individuals with intellectual disability may differ in the kind of spatial knowledge they extract from the environment and/or in the strategy they use to learn routes