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Published on: March 1, 2017
Problem difficulty and expertise modulate planning performance in a virtually embodied task
Riccardo Moretti1,2, Jeremy Gordon3, Antonella Maselli4
1Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy.
None:
Expertise in cognitively and motorically demanding tasks, such as indoor climbing and bouldering, is often associated with enhanced planning abilities, yet the specific relationship between cognitive and motor planning in such tasks remains underexplored. This study investigates how expertise influences route planning in bouldering, with a focus on the impact of problem difficulty. We asked expert and novice climbers to virtually solve easy and hard bouldering problems on a familiar indoor climbing wall, using a custom app that allowed them to plan and select sequences of hand movements. Our results show that climbers are slower and less accurate in solving problems that are harder to climb, despite sharing the same perceptual features with easier problems, suggesting a link between the motoric difficulty of solving problems and the accuracy of planning them. Furthermore, expert climbers made fewer severe planning errors and solved problems faster than novices, indicating an advantage in planning ability beyond physical climbing skills. Interestingly, novice climbers were more likely to make short-sighted planning errors in easy problems, opting for nearby holds that were not part of the correct sequence. These findings extend our understanding of how expertise modulates the relationship between cognitive and motor planning, highlighting the role of planning depth and strategy in physically constrained environments. The study also suggests that future research should explore the mechanisms supporting route planning, such as embodied simulation, to better understand the cognitive and motor processes underlying expert performance in dynamic, embodied tasks.NEW & NOTEWORTHY This study investigates the way climbing expertise shapes planning across varying problem difficulties. Using a novel virtual route-planning tool, the study reveals that participants are less accurate and slower when planning how to solve hard problems. Furthermore, experts plan more accurately and efficiently and avoid short-sighted errors that novices make with higher frequency. These findings highlight how problem difficulty and expertise influence planning accuracy in virtually embodied environments.
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