Effects of input quality on ASL vocabulary acquisition in deaf children

输入质量对聋哑儿童 ASL 词汇习得的影响

• 批准号: 10404733
• 负责人: Naomi K. Caselli
• 金额: $ 24.75万
• 依托单位: BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-08 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10404733
• 关键词: Address; Administrator; Affect; American Sign Language; Boston; COVID-19; Child; Clip; Code; Cognition; Collection; Computer software; Custom; Data; Data Collection; Data Set; Databases; Exposure to; Film; Funding; Goals; Individual; Intervention; Label; Language; Language Delays; Language Development; Language Tests; Measures; Metadata; Methods; Mind; Modification; Names; Paper; Participant; Persons; Process; Readability; Research; Research Personnel; Risk; Secure; Semantics; Sign Language; Software Engineering; Source Code; Statutes and Laws; System; Testing; Text; Time; Training; Universities; Vocabulary; Work; base; cloud based; data resource; deaf; design; early childhood; experience; innovation; lexical; online delivery; open source; parent grant; parent project; research study; response; skills; software development; tool; web site

The goal of the parent grant is to understand how language input during early childhood affects vocabulary acquisition in American Sign Language (ASL). As part of the parent grant, we have developed three ASL assessments for young deaf children. One was originally intended to be delivered online and made publicly available as a major initiative in the parent grant (the ASL-CDI 2.0), and the other two were intended to be delivered in person (the EEAT and the ERAT). Because of COVID-19, administering the EEAT and ERAT has become unwieldy, and an alternate method of delivering them is needed. As part of an NSF-funded project, we already developed a platform called SignLab for collecting and coding video data for a specific research study. The specific aims of the supplement are 1) to use the code base from SignLab to convert it from a single-use product to a platform that researchers could use to collect and code video data of all kinds, 2) to use SignLab to deliver the EEAT and ERAT, and 3) to enable researchers and clinicians to access, administer, and track results from the EEAT and ERAT. This software will serve two purposes. It will remove significant barriers in the field of sign language research, making it much more efficient to develop large-scale machine-readable sign language datasets. Additionally, the vast majority of deaf children are at risk for delayed language acquisition, and making the EEAT and ERAT widely accessible will help clinicians, states, and researchers identify language delays early when interventions are most effective.

家长补助金的目标是了解幼儿时期的语言输入如何影响词汇量 美国手语（ASL）作为家长补助金的一部分，我们制定了三个ASL 对年幼聋哑儿童的评估。一个原本打算在线交付并公开 作为父母补助金（ASL-CDI 2.0）中的一项主要举措提供，另外两项旨在 人，是人。由于COVID-19，管理EEAT和ERAT 变得笨重，需要一种替代的方法来输送它们。作为NSF资助项目的一部分，我们 已经开发了一个名为SignLab的平台，用于收集和编码特定研究的视频数据。 补充的具体目标是1）使用SignLab的代码库将其从一次性使用转换为 产品的平台，研究人员可以用来收集和编码各种视频数据，2）使用SignLab 提供EEAT和ERAT，3）使研究人员和临床医生能够访问、管理和跟踪 EAT和ERAT的结果。这个软件有两个目的。它将消除重大障碍， 手语研究领域，使其更有效地开发大规模的机器可读 手语数据集。此外，绝大多数聋哑儿童都有语言延迟的风险。 获取，并使EEAT和ERAT广泛使用将有助于临床医生，国家和研究人员 在干预措施最有效的时候及早发现语言障碍。