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Can We Improve Structured Sequence Processing? Exploring the Direct and Indirect Effects of Computerized Training Using a Mediational Model

机译:我们可以改善结构化序列处理吗?使用中介模型探索计算机培训的直接和间接效果

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摘要

Recent research suggests that language acquisition may rely on domain-general learning abilities, such as structured sequence processing, which is the ability to extract, encode, and represent structured patterns in a temporal sequence. If structured sequence processing supports language, then it may be possible to improve language function by enhancing this foundational learning ability. The goal of the present study was to use a novel computerized training task as a means to better understand the relationship between structured sequence processing and language function. Participants first were assessed on pre-training tasks to provide baseline behavioral measures of structured sequence processing and language abilities. Participants were then quasi-randomly assigned to either a treatment group involving adaptive structured visuospatial sequence training, a treatment group involving adaptive non-structured visuospatial sequence training, or a control group. Following four days of sequence training, all participants were assessed with the same pre-training measures. Overall comparison of the post-training means revealed no group differences. However, in order to examine the potential relations between sequence training, structured sequence processing, and language ability, we used a mediation analysis that showed two competing effects. In the indirect effect, adaptive sequence training with structural regularities had a positive impact on structured sequence processing performance, which in turn had a positive impact on language processing. This finding not only identifies a potential novel intervention to treat language impairments but also may be the first demonstration that structured sequence processing can be improved and that this, in turn, has an impact on language processing. However, in the direct effect, adaptive sequence training with structural regularities had a direct negative impact on language processing. This unexpected finding suggests that adaptive training with structural regularities might potentially interfere with language processing. Taken together, these findings underscore the importance of pursuing designs that promote a better understanding of the mechanisms underlying training-related changes, so that regimens can be developed that help reduce these types of negative effects while simultaneously maximizing the benefits to outcome measures of interest.
机译:最近的研究表明,语言习得可能依赖于领域通用的学习能力,例如结构化序列处理,即在时间序列中提取,编码和表示结构化模式的能力。如果结构化序列处理支持语言,则可以通过增强这种基础学习能力来改善语言功能。本研究的目的是使用一种新颖的计算机培训任务作为一种手段,以更好地理解结构化序列处理和语言功能之间的关系。首先,对参与者进行了培训前任务评估,以提供结构化序列处理和语言能力的基线行为测量。然后将参与者准随机分配到一个涉及自适应结构化视觉空间序列训练的治疗组,一个涉及自适应非结构​​化视觉空间序列训练的治疗组或一个对照组。在进行为期四天的序列训练之后,所有参与者均接受了相同的训练前评估。培训后方式的总体比较表明,没有群体差异。但是,为了检查序列训练,结构化序列处理和语言能力之间的潜在关系,我们使用了调解分析,该分析显示了两种竞争效果。在间接影响下,具有结构规律性的自适应序列训练对结构化序列处理性能具有积极影响,而反过来又对语言处理产生积极影响。这一发现不仅确定了治疗语言障碍的一种潜在的新颖干预手段,而且可能是第一个证明,可以改善结构化序列处理,进而影响语言处理。然而,直接的效果是,具有结构规则性的自适应序列训练对语言处理产生了直接的负面影响。这一出乎意料的发现表明,具有结构规律性的自适应训练可能会干扰语言处理。综上所述,这些发现强调了追求设计的重要性,这些设计可以促进更好地理解与培训相关的变化的潜在机制,因此可以制定出有助于减少此类负面影响的方案,同时最大程度地提高目标结果度量的收益。

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