RESEARCH ARTICLE


The Nonlinear Nature of Learning - A Differential Learning Approach



W. I. Schollhorn*, 1, P. Hegen1, K. Davids2
1 University of Mainz, Institute for Sport Science, Albert Schweitzer Straße 22, 55099 Mainz, Germany
2 Queensland University of Technology, Australia


Article Metrics

CrossRef Citations:
86
Total Statistics:

Full-Text HTML Views: 1735
Abstract HTML Views: 3225
PDF Downloads: 1032
Total Views/Downloads: 5992
Unique Statistics:

Full-Text HTML Views: 1088
Abstract HTML Views: 1689
PDF Downloads: 786
Total Views/Downloads: 3563



Creative Commons License
© 2012 I. Schollhorn et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the University of Mainz, Institute for Sport Science Albert Schweitzer Straße 22, 55099 Mainz, Germany; Tel: 06131 3923583; Fax: 06131 3920643; E-mail: schoellw@uni-mainz.de


Abstract

Traditional learning approaches are typically based on a linear understanding of causality where the same cause leads to the same effect. In recent years there has been increasing interest in the complexity of nature and living phenom-ena, with significant insights provided by models of change that are based on a nonlinear understanding of causality, where small causes can lead to big effects and vice versa. In this vein, learning processes seem to be more successful for inducing behavioral change when teaching processes deviate from a linear approach. The differential learning approach takes advantage of fluctuations in a complex system by increasing them through ‘no repetition’ and ‘constantly changing movement tasks’ which add stochastic perturbations. Previous research has provided much evidence on the superiority of a differential learning approach for learning single movement techniques, in comparison to repetition- and correction-oriented approaches. In this pilot study, the parallel acquisition and learning of two movement techniques in the sport of football are the objective of investigation. One traditionally trained group and two differentially trained groups (blocked and random) trained for 4 weeks, twice a week, on ball control and shooting at goal tasks. Results supported previous work and revealed significant advantages for both differential groups in the acquisition phase as well as in the learning phase, compared to the traditional group. These data suggest that, instead of following a direct linear path towards the tar-get of a ‘to-be-learned’ movement technique by means of numerous repetitions and corrections, a differential approach is more beneficial because it perturbs learners towards more functional movement patterns during practice.

Keywords: Differential Learning, complex systems, fluctuations, football, movement variability.