Suppr超能文献

使用矩阵训练促进自闭症儿童的生成性语言。

The use of matrix training to promote generative language with children with autism.

作者信息

Frampton Sarah E, Wymer Sarah C, Hansen Bethany, Shillingsburg M Alice

机构信息

Marcus Autism Center.

Marcus Autism Center and Emory University School of Medicine.

出版信息

J Appl Behav Anal. 2016 Dec;49(4):869-883. doi: 10.1002/jaba.340. Epub 2016 Jul 29.

Abstract

Matrix training consists of planning instruction by arranging components of desired skills across 2 axes. After training with diagonal targets that each combine 2 unique skill components, responses to nondiagonal targets, consisting of novel combinations of the components, may emerge. A multiple-probe design across participants was used to evaluate matrix training with known nouns (e.g., cat) and verbs (e.g., jumping) with 5 children with autism spectrum disorders (ASD). Following baseline of Matrix 1 and a generalization matrix, diagonal targets within Matrix 1 were trained as noun-verb combinations (e.g., cat jumping). Posttests showed recombinative generalization within Matrix 1 and the generalization matrix for 4 participants. For 1 participant, diagonal training across multiple matrices was provided until correct responding was observed in the generalization matrix. Results support the use of matrix training to promote untrained responses for learners with ASD and offer a systematic way to evaluate the extent of generalization within and across matrices.

摘要

矩阵训练包括通过在两个轴上安排所需技能的组成部分来规划指导。在用每个都结合了两个独特技能组成部分的对角线目标进行训练后,可能会出现对由这些组成部分的新组合构成的非对角线目标的反应。采用跨参与者的多探针设计,对5名自闭症谱系障碍(ASD)儿童进行了关于已知名词(如“猫”)和动词(如“跳跃”)的矩阵训练评估。在矩阵1的基线和一个泛化矩阵之后,矩阵1内的对角线目标被训练为名词 - 动词组合(如“猫跳跃”)。后测显示,4名参与者在矩阵1和泛化矩阵内出现了重组泛化。对于1名参与者,提供了跨多个矩阵的对角线训练,直到在泛化矩阵中观察到正确反应。结果支持使用矩阵训练来促进ASD学习者的未训练反应,并提供了一种系统的方法来评估矩阵内和跨矩阵的泛化程度。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验