Processing Measures LI--Linguistically Diverse Learners

描述（由申请人提供）：该探索性项目的目标是开发和完善一套新的基于加工的测量工具，可用于有效识别具有不同语言学习经历的儿童的主要或“特定”语言障碍（LI）的行为表型。与会者将只讲英语，有和没有LI，西班牙语和英语的双语发言者，苗族和英语的双语发言者。我们提出了两种类型的任务，强调语言处理或非语言信息的处理。这三个基于语言的加工任务是非词重复、计数广度和快速命名，分别用英语、西班牙语和苗族语进行。3个非语言加工任务是选择视觉检测、听觉序列记忆和Tallal重复。将使用组比较和似然比计算任务敏感性和特异性。逻辑回归和聚类分析将用于确定识别LI儿童和潜在LI亚组的最佳任务组合。本研究应用的创新是2倍：采取基本步骤的语言多样性的背景下，解决LI表型和开发评估措施，利用强大的方面的信息处理系统，也就是说，检查伴随LI语言性能的非语言认知概况以及更明显的语言处理缺陷。从拟议的项目的结果将直接有助于一个更明确定义的LI表型，以及发展的非偏见的评估措施，需要分离典型的语言发展LI在日益多样化的人口。

DESCRIPTION (provided by applicant): The goal of this exploratory project is to develop and refine a novel battery of processing-based measurement tools that can be used to effectively identify a behavioral phenotype for primary or "specific" language impairment (LI) across children with diverse language learning experiences. Participants will be English-only speakers with and without LI, bilingual speakers of Spanish and English, and bilingual speakers of Hmong and English. We propose 2 types of tasks that emphasize either language processing or the processing of nonlinguistic information. The 3 language-based processing tasks are non-word repetition, counting span and rapid naming, in English, Spanish and Hmong. The 3 non-linguistic processing tasks are choice visual detection, auditory serial memory, and Tallal repetition. Group comparisons followed by likelihood ratios will be used to calculate task sensitivity and specificity. Logistic regression and cluster analyses will be used to determine the best combination of tasks for identifying children with LI and potential LI subgroups. The innovation of this research application is 2-fold: to take the fundamental step of addressing the LI phenotype within the context of linguistic diversity and to develop assessment measures that tap into robust aspects of the information processing system, that is, to examine the nonlinguistic cognitive profile accompanying LI language performance as well as the more observable deficit in language processing. Results from the proposed project will directly contribute to a more clearly defined LI phenotype as well as to the development of non-biased assessment measures needed for separating typical language development from LI in an increasingly diverse population.