Novices Make More Noise!
The D&K Effect 2.0?
Jan Schneider (DIPF - Leibniz Institute for Research and Information in Education)
Khaleel Asyraaf Mat Mat Sanusi (Cologne University of Applied Sciences)
B.H. Limbu (TU Delft - Web Information Systems)
Marcel Schmitz (Zuyd University of Applied Science)
Daniel Schiffner (DIPF - Leibniz Institute for Research and Information in Education)
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Abstract
This paper presents an approach that helps distinguish expert and novice performance easily by observing the sensor data without having to understand nor apply models to the sensor signal. The method consists of plotting the sensor data and identifying irregularities. We corroborate, with the help of sensors, that expert performances are smoother, contain fewer irregularities, and have consistently uniform patterns than novice performances. In this paper, we present six different cases pointing out this assertion, namely bachata and salsa dances, tennis swings, football penalty kicks, badminton, and running.
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