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Transfer of complex skill learning from virtual to real rowing.

Georg Rauter1, Roland Sigrist1, Claudio Koch1

  • 1Sensory-Motor Systems (SMS) Lab, Institute of Robotics and Intelligent Systems (IRIS), ETH Zurich, Zurich, Switzerland ; Medical Faculty, University of Zurich, Zurich, Switzerland.

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Realistic sculling simulators effectively train rowing skills, demonstrating significant skill transfer to on-water performance. This research validates simulator training for complex motor skills.

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Area of Science:

  • Sports Science
  • Human-Computer Interaction
  • Motor Learning

Background:

  • Simulators are widely used for training complex tasks, including dangerous ones, for cost savings and performance analysis.
  • However, the effectiveness of simulator training is often unproven due to a lack of investigation into skill transfer to real-world tasks.
  • Without validated skill transfer, simulators may be ineffective or even detrimental to learning.

Purpose of the Study:

  • To investigate the skill transfer of complex technical aspects from a scull rowing simulator to on-water sculling.
  • To determine if high-fidelity simulator training, even without augmented feedback, leads to comparable skill gains and transfer as real-world training.

Main Methods:

  • Two groups of recreational rowers (n=4 each) underwent four training sessions over two weeks.
  • One group trained on a sculling simulator, the other on water, both with the same trainer.
  • Performance was assessed using quantitative biomechanical measures and qualitative video evaluations by a blinded, independent trainer.

Main Results:

  • Both simulator and on-water training groups improved performance.
  • Biomechanical measures offered limited insight into development; qualitative video evaluation provided a better overall impression.
  • Participants confirmed the simulator's high quality and naturalism.

Conclusions:

  • Realistic simulator training yields skill gains comparable to real-world training.
  • Simulator training effectively enables skill transfer to the actual task.
  • Future work can enhance motor learning through simulator training combined with augmented feedback.