SBIR Phase I: READ! Toolkit, A Knowledge-Based Expert System to Develop Beginning Literacy Curricula in Endangered or Underserved Languages

SBIR 第一阶段：阅读！

• 批准号: 1842833
• 负责人: Catherine Callow-Heusser
• 金额: $ 22.5万
• 依托单位: BETTERMENT LABS, L.L.C.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-01-01 至 2019-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1842833&HistoricalAwards=false
• 关键词: SBIR; Phase; READ; Toolkit; Knowledge

This SBIR Phase I project will develop and test a computer-based expert system that will guide development of beginning literacy curricula in any phonics-based language. The system will produce beginning literacy curricula mobile apps for phones and tablets and will include beginning reading, writing, vocabulary-building, and assessment activities. The expert system will (a) minimize cost, time and expertise required to develop early literacy curricula, (b) produce curricula that could increase early reading fluency and bilingualism, which is related to children's improved ability to manage their thoughts, behaviors and emotions, (c) provide effective curricula to learn languages other than English at home or school, (d) revitalize endangered or underserved languages while increasing connections to culture and heritage, which will improve long-term academic, health and economic outcomes for indigenous children or children who speak a language other than English at home, and increase their participation in STEM careers, and (e) contribute to research on bilingualism's impacts on academic, social, emotional, and cultural outcomes. The system will be licensed by underserved language communities, tribes, individuals, and organizations interested in improving literacy, with revenue produced by the mobile app products developed using the expert system shared between curriculum developers and the expert system developer.This SBIR Phase I project will develop and test a knowledge-based expert system that integrates early literacy research; language analysis to provide evidence-based recommendations for developing decodable text for phonics-based early literacy curricula; evidence-based teaching and formative assessment strategies; curriculum development knowledge; user interface/user experience best-practices; natural language processing for pronunciation feedback; and database and technology skills to guide users who may not have the knowledge and skills in developing a beginning literacy curricula in any language. The best practices and methods based on the research will be incorporated by analyzing text to create lists of sounds/letters and words, their frequencies, and sounds and words that come before and after each sound/word. From these lists, the system will generate language-specific recommendations based on the rules for optimal sequencing of sounds and words for learning to decode in another language. While some evidence-based guidelines needed for decoding in English, which is less phonetically regular than many underserved languages, may not apply in a language that is more phonetically regular, most are expected to. These rules will guide recommendations from which users of the knowledge-based expert system can select sequences sounds, words, and phrases to write decodable, connected text, culturally relevant stories for beginning literacy curricula.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这个SBIR I阶段项目将开发和测试基于计算机的专家系统，该系统将指导以任何基于语音的语言的语言开发扫盲课程的开发。该系统将为手机和平板电脑生产开始的扫盲课程移动应用程序，包括开始阅读，写作，词汇构建和评估活动。专家系统将（a）最大程度地减少开发早期识字课程所需的成本，时间和专业知识，（b）制作课程，可以增加早期阅读的流利和双语主义，这与儿童改善的思想，行为和情感的能力相关，（c）在国内培养或不断培养的语言中，（d）提供有效的语言，（c）提供有效的语言，（d），（d）培养的语言，（d）（d），（d）（d），（d）（d）（d），（d）（d），（D）对于在家中说英语以外的其他语言，增加对STEM职业的参与，以及（e）对双语主义对学术，社会，情感和文化成果的影响的研究，对本地儿童或讲语言以外的其他语言的长期学术，健康和经济成果。该系统将获得服务不足的语言社区，部落，个人和组织有兴趣提高识字率的许可，并使用课程开发人员与专家系统开发人员之间共享的专家系统开发的移动应用产品产生的收入。该SBIR I阶段I阶段项目将开发和测试基于知识的知识系统，以集成早期识字研究；语言分析提供基于证据的建议，以开发用于基于语音的早期扫盲课程的可解码文本；基于证据的教学和形成性评估策略；课程发展知识；用户界面/用户体验最佳实践；发音反馈的自然语言处理；数据库和技术技能可以指导那些可能没有任何语言开发初学扫盲课程的知识和技能的用户。基于研究的最佳实践和方法将通过分析文本来创建声音/字母和单词，它们的频率以及每个声音/单词之前和之后出现的声音和单词的列表来纳入。从这些列表中，系统将根据规则来生成特定于语言的建议，以最佳测序声音和单词以学习用另一种语言进行解码。尽管用英语解码所需的一些基于证据的指南，而语音上的规律性不及许多服务不足的语言，但可能不适用于更常规的语言，大多数人都可以预期。这些规则将指导建议，基于知识的专家系统的用户可以选择序列，单词和短语来撰写可解码的，连接的文本，文化上相关的故事，以开始识字课程。该奖项反映了NSF的法定任务，并认为通过使用基金会的知识分子和更广泛的影响来审查Criteria通过评估，可以通过评估来获得支持。