Ammar Achraf, Salem Atef, Simak Marvin Leonard, Horst Fabian, Schöllhorn Wolfgang I
Department of Training and Movement Science, Institute of Sport Science, Johannes Gutenberg-University Mainz, Mainz, Germany.
Research Laboratory, Molecular Bases of Human Pathology, LR19ES13, Faculty of Medicine of Sfax,University of Sfax, Sfax 3029, Tunisia.
Biol Sport. 2025 Jan;42(1):151-161. doi: 10.5114/biolsport.2025.141662. Epub 2024 Jul 31.
Despite the development of various motor learning models over many decades, the question of which model is most effective under which conditions to optimize the acquisition of skills remains a heated and recurring debate. This is particularly important in connection with learning sports movements with a high strength component. This study aims to examine the acute effects of various motor learning models on technical efficiency and force production during the Olympic snatch movement. In a within-subject design, sixteen highly active male participants (mean age: 23.13 ± 2.09 years), who were absolute beginners regarding the learning task, engaged in randomized snatch learning bouts, consisting of 36 trials across different learning models: differential learning (DL), contextual interference (serial, sCI; and blocked, bCI), and repetitive learning (RL). Kinematic and kinetic data were collected from three snatch trials executed following each learning bout. Discrete data from the most commonly monitored biomechanical parameters in Olympic weightlifting were analyzed using inferential statistics to identify differences between learning models. The statistical analysis revealed no significant differences between the learning models across all tested parameters, with p-values ranging from 0.236 to 0.99. However, it was observed that only the bouts with an exercise sequence following the DL model resulted in an average antero-posterior displacement of the barbell that matched the optimal displacement. This was characterized by a mean positive displacement towards the lifter during the pulling phases, a negative displacement away from the lifter in the turnover phase, and a return to positive displacement in the catch phase. These findings indicate the limited acute impact of the exercise sequences based on the three motor learning models on Olympic snatch technical efficiency in beginners, yet they hint at a possible slight advantage for the DL model. Coaches might therefore consider incorporating the DL model to potentially enhance technical efficiency, especially during the early stages of skill acquisition. Future research, involving even bigger amounts of exercise noise, longer learning periods, or a greater number of total learning trials and sessions, is essential to verify the potential advantages of the DL model for weightlifting technical efficiency.
尽管几十年来已经开发了各种运动学习模型，但哪种模型在何种条件下最有效地优化技能习得的问题仍然是一个激烈且反复出现的争论焦点。这在学习具有高强度成分的运动动作时尤为重要。本研究旨在检验各种运动学习模型对奥林匹克抓举动作期间技术效率和力量产生的急性影响。在一项被试内设计中，16名高度活跃的男性参与者（平均年龄：23.13±2.09岁），他们对于学习任务而言是绝对的初学者，参与了随机抓举学习回合，包括跨不同学习模型的36次试验：差异学习（DL）、情境干扰（序列式，sCI；和组块式，bCI）以及重复学习（RL）。在每个学习回合之后进行的三次抓举试验中收集运动学和动力学数据。使用推断统计分析来自奥林匹克举重中最常监测的生物力学参数的离散数据，以确定学习模型之间的差异。统计分析显示，在所有测试参数上，学习模型之间没有显著差异，p值范围从0.236到0.99。然而，观察到只有遵循DL模型的练习序列回合导致杠铃的平均前后位移与最佳位移相匹配。其特征是在提拉阶段朝向举重者的平均正向位移、在翻腕阶段远离举重者的负向位移以及在接杠阶段回到正向位移。这些发现表明基于这三种运动学习模型的练习序列对初学者奥林匹克抓举技术效率具有有限的急性影响，但它们暗示了DL模型可能具有轻微优势。因此，教练可能会考虑纳入DL模型以潜在地提高技术效率，特别是在技能习得的早期阶段。未来的研究，涉及更多的运动干扰、更长的学习期或更多的总学习试验和训练课，对于验证DL模型对举重技术效率的潜在优势至关重要。
