Gray Rob
Human Systems Engineering, Arizona State University Polytechnic Campus, Mesa, AZ, United States.
Front Psychol. 2017 Dec 13;8:2183. doi: 10.3389/fpsyg.2017.02183. eCollection 2017.
The use of virtual environments (VE) for training perceptual-motors skills in sports continues to be a rapidly growing area. However, there is a dearth of research that has examined whether training in sports simulation transfers to the real task. In this study, the transfer of perceptual-motor skills trained in an adaptive baseball batting VE to real baseball performance was investigated. Eighty participants were assigned equally to groups undertaking adaptive hitting training in the VE, extra sessions of batting practice in the VE, extra sessions of real batting practice, and a control condition involving no additional training to the players' regular practice. Training involved two 45 min sessions per week for 6 weeks. Performance on a batting test in the VE, in an on-field test of batting, and on a pitch recognition test was measured pre- and post-training. League batting statistics in the season following training and the highest level of competition reached in the following 5 years were also analyzed. For the majority of performance measures, the adaptive VE training group showed a significantly greater improvement from pre-post training as compared to the other groups. In addition, players in this group had superior batting statistics in league play and reached higher levels of competition. Training in a VE can be used to improve real, on-field performance especially when designers take advantage of simulation to provide training methods (e.g., adaptive training) that do not simply recreate the real training situation.
利用虚拟环境(VE)来训练运动中的感知运动技能仍是一个快速发展的领域。然而,对于体育模拟训练能否迁移到实际任务,相关研究却很匮乏。在本研究中,我们调查了在自适应棒球击球虚拟环境中训练的感知运动技能向实际棒球表现的迁移情况。80名参与者被平均分配到四组,分别进行虚拟环境中的自适应击球训练、虚拟环境中的额外击球练习、实际的额外击球练习,以及不进行额外训练(仅进行常规练习)的对照组。训练为期6周,每周进行两次,每次45分钟。在训练前后,分别测量参与者在虚拟环境中的击球测试、实地击球测试以及投球识别测试中的表现。我们还分析了训练后那个赛季的联赛击球数据,以及接下来5年中达到的最高比赛水平。对于大多数表现指标而言,与其他组相比,自适应虚拟环境训练组在训练前后的进步显著更大。此外,该组球员在联赛中的击球数据更优,达到的比赛水平也更高。在虚拟环境中进行训练可用于提高实际的场上表现,尤其是当设计者利用模拟来提供并非简单重现实际训练情境的训练方法(如自适应训练)时。