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Abstract: Schematic maps are an important component of assistance for navigating transport networks worldwide. By showing routes as simple straight lines, they reduce the cognitive load of journey planning, and by revealing the underlying structure of networks, they make their key features easier to identify and learn. However, although there are many suggestions for optimizing schematic maps so as to maximize these benefits, to date these have not been directly supported by published usability studies or psychological theory. In this paper, we suggest that there are circumstances in which conventional schematic maps fail to yield benefits, and we compare journey planning using the current official RATP Paris Metro map with an all-curves design which replaces straight lines and corners with gentle curves. Three separate usability studies with slightly different methodologies showed that the journey planning time for the all-curves map was better than the RATP version, with effect sizes ranging from 0.48 to 1.12. Subjective usability ratings were derived from questionnaires, and user preferences, but neither were correlated with objective usability measures. We conclude that (1) in terms of designing schematics, there is no evidence to suggest that any rule-set can be claimed to be a gold-standard, and it is important to match the design rules to the properties of the network, (2) in some circumstances, radical departures from traditional ideas can yield usability benefits, and (3) map usability appears to be distinct from map engagement, although the latter is undoubtedly important in encouraging people fully to make use of navigation aides. [Copyright &y& Elsevier]

• Complex span tasks with simple stimuli represent working memory. • Processing times in complex span tasks explain variance in high-level cognition. • Time available for maintenance explains down-stream variance in high-level cognition, but not working memory storage. • Attentional resources and time-based maintenance are both important in working memory and high-level cognition. • Resource-sharing and task-switching accounts best explain the WM-HLC relationship. This study examined working memory (WM) using complex span tasks (CSTs) to improve theoretical understanding of the relationship between WM and high-level cognition (HLC) in children. A total of 92 children aged 7 and 8 years were tested on three computer-paced CSTs and measures of nonverbal reasoning, reading, and mathematics. Processing times in the CSTs were restricted based on individually titrated processing speeds, and performance was compared with participant-led tasks with no time restrictions. Storage, processing accuracy, and both processing and recall times within the CSTs were used as performance indices to understand the effects of time restrictions at a granular level. Restricting processing times did not impair storage, challenging models that argue for a role of maintenance in WM. A task-switching account best explained the effect of time restrictions on performance indices and their interrelationships. Principal component analysis showed that a single factor with all performance indices from just one CST (counting span) was the best predictor of HLC. Storage in both the participant-led and computer-paced versions of this task explained unique and shared variance in HLC. However, the latter accounted for more variance in HLC when contributions from processing time were included in the model. Processing time in this condition also explained variance above and beyond storage. This suggests that faster processing is important to keep information active in WM; however, this is evident only when time restrictions are placed on the task and important when WM performance is applied in broader contexts that rely on this resource. [ABSTRACT FROM AUTHOR]