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.

家长资助的目标是了解幼儿时期的语言输入如何影响词汇量 习得美国手语（ASL）。作为家长资助的一部分，我们开发了三种 ASL 对年幼聋哑儿童的评估。一份原本打算在网上发布并公开发布 作为父赠款（ASL-CDI 2.0）中的一项主要举措，其他两项旨在 亲自交付（EEAT 和 ERAT）。由于 COVID-19，实施 EEAT 和 ERAT 已 变得笨拙，并且需要一种替代方法来传递它们。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。 该补充的具体目标是 1) 使用 SignLab 的代码库将其从一次性使用转换为 产品到研究人员可以用来收集和编码各种视频数据的平台，2) 使用 SignLab 提供 EEAT 和 ERAT，以及 3) 使研究人员和临床医生能够访问、管理和跟踪 EEAT 和 ERAT 的结果。该软件有两个用途。它将消除重大障碍 手语研究领域，使大规模机器可读的开发更加高效 手语数据集。此外，绝大多数聋哑儿童面临语言迟缓的风险 获取 EEAT 和 ERAT 并使其广泛使用将有助于临床医生、州政府和研究人员 当干预措施最有效时，及早发现语言发育迟缓。