Skill acquisition and cue-based processing

Over the last several decades, research across a number of practice domains has suggested that the advanced perceptual-cognitive skills or cue utilisation of experts enables these operators to excel in tasks that rely upon anticipatory decisions and the formation of rapid responses. Indeed, skilled performance itself has been characterised by rapid and accurate responses, often in complex and dynamic situations. These specialised associations, which represent situation-specific relationships between environmental features and outcomes or objects and which lie resident in memory, are referred to as cues. However, while cue utilisation is typically considered a pattern recognition or associational process, the specific cognitive mechanisms that underlie cue utilisation remain unclear. The present programme of research was designed to investigate the nature of cue utilisation and examine the mechanisms that underlie cue utilisation in the early stages of learning a new task/skill. Study 1 was conducted with the aim of investigating the impact of cue utilisation on performance, using a simplified rail control task. The results indicated that there were significant differences in the performance of participants with higher and lower cue utilisation. Throughout the 20-minute rail task, the mean response latency of participants with higher cue utilisation remained significantly higher, compared to participants with lower cue utilisation. One explanation for these results was that the decision to re-route trains in the rail task could be initiated up to seven seconds from the appearance of a train, and therefore, participants with greater cue utilisation may have recognised this opportunity and utilised the additional time. To test this explanation, a similar methodology was adopted in Study 2, but with the inclusion of a secondary task to invoke an explicit cognitive load part-way through the simulated rail control task. Throughout the initial stage of the rail task, the performance of participants was consistent with the results from Study 1, whereby the response latency recorded was higher for participants with higher cue utilisation. However, once the secondary task was initiated, the response latencies of participants with lower cue utilisation increased, while the response latency amongst participants with higher cue utilisation remained relatively consistent. These results provided support for the view that participants with higher cue utilisation identified cues in the environment (e.g., decision-time availability) that allowed them some advantage, reducing the demands on cognitive load, and thereby enabling their performance to be less impacted by an increase in cognitive demands. Study 3 was designed to examine whether the performance of participants with relatively greater cue utilisation during the simulated rail control task, reflected strategies to reduce cognitive load, or whether a reduction in cognitive load represented an outcome of the process to achieve cue utilisation. A primary difference in Study 3 was the inclusion of a pattern in the rail task. Trains were programmed to appear in a particular sequence, and trains on only two of the four tracks required a diversion. Importantly, this pattern was not disclosed to participants. The results indicated that, under higher workload conditions, participants with higher cue utilisation were least affected by the imposition of the secondary task (they made fewer errors and were faster to respond in the rail task). Further, the participants in the higher cue group were eleven times more likely than those in the lower cue group, to accurately report the rail pattern. The results of Study 3 suggested that greater cue utilisation during a novel, simulated rail control task, reflected pattern-recognition mechanisms which resulted in a reduction of cognitive load. Extending these findings, Study 4 was designed to examine whether the relationship between cue utilisation and rail task performance depended upon pattern recognition (a moderating relationship) and whether individuals who have higher cue utilisation and who rapidly acquire task-related patterns, also have an increased tendency toward miscueing. Study 4 included three different patterns of rail movement and each was programmed to change abruptly during the course of the twenty-four-minute rail task. It was reasoned that if participants who acquired the pattern were reliant on the pattern to formulate fast and accurate train diversions, the initial, abrupt change to this pattern would represent a miscue, and result in a temporary reduction in performance evident in slower responses and reduced accuracy. The results provided support for this hypothesis. Participants with higher cue utilisation were 2.9 times more likely to identify the train pattern. Further, compared to participants with lower cue utilisation and for participants who verbally identified the rail pattern, higher cue utilisation was associated with an increase in mean response latency to the initial miscue. However, for participants who did not identify the pattern, no relationship was evident. These findings suggest that the capacity to detect and respond to task-related patterns acts as the underlying mechanism that explains the impact of cue utilisation on task performance. The results of Study 4 also suggested that a capacity for high cue utilisation and an ability to rapidly detect patterns of dynamic stimuli, can give rise to miscueing in environments that are typically marked by regularity and routine.