Is Prescription of Specific Movement Form Necessary for Optimal Skill Development? A Nonlinear Pedagogy Approach

ABSTRACT

Purpose: Nonlinear Pedagogy (NLP) proposes that skill development is a nonlinear process, advocating the integration of variability into practice to facilitate individualized movement patterns. However, the influence of a NLP for skills that emphasize a specific movement form is relatively unknown. This study aimed to investigate the impact of a NLP approach when learning a movement form based skill. Method: Sixteen beginners in the power clean (PC), were randomly assigned into a linear pedagogy (LP) condition receiving instructions that prescribed explicit movement form, and a NLP condition presented with analogy-based instructions and two task constraints. Both conditions completed seven lessons across 4-weeks. Results: There were no significant differences in the quantity of exploration, with both conditions demonstrating a similar range of movement patterns. These findings were coupled with a significant improvement in performance accuracy (reduced forward movement of the barbell; F × D) for both conditions. No significant differences were detected in the distribution of barbell trajectory types, with type one, three and four trajectories being exhibited to a similar degree in both conditions. Conclusion: Findings from this study suggests both NLP and LP pedagogies can successfully develop movement form based skills. Overall, both NLP and LP approaches appear to positively influence skill development. These findings have important implications for practitioners suggesting that deviations from instructed technique in learners (i.e., LP approach) do not negatively impact performance. However, further research is needed to determine whether these approaches can more effectively facilitate learners’ search for movement solutions that “fit” their individual abilities.

KEYWORDS:

• Nonlinear pedagogy
• motor exploration
• motor skills
• skill acquisition
• task constraint

Acknowledgments

We would like to thank the biomechanics laboratory team at Victoria University, specifically Shannon Barnes, Azadeh Kian, and Rhett Stephens, for their continual support and assistance throughout the data collection phase of the study.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability

The data that support the findings of this study are available from the corresponding author, upon reasonable request.

Supplementary material

Supplemental data for this article can be accessed on the publisher’s website.

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

The authors reported there is no funding associated with the work featured in this article.