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

SBIR第一阶段项目将开发和测试一个以计算机为基础的专家系统，该系统将指导以任何以语音为基础的语言编写初级扫盲课程。该系统将为手机和平板电脑制作初级识字课程移动应用程序，并将包括初级阅读、写作、词汇建设和评估活动。专家系统将：(A)最大限度地减少制定早期扫盲课程所需的成本、时间和专门知识；(B)编制能够提高早期阅读流利性和双语能力的课程，这与儿童管理其思想、行为和情绪的能力有关；(C)提供有效的课程，以便在家里或学校学习英语以外的语言；(D)振兴濒危或服务不足的语言，同时加强与文化和遗产的联系，这将改善土著儿童或在家中说英语以外语言的儿童的长期学术、健康和经济成果，并增加他们对STEM职业的参与，以及(E)致力于研究双语对学术、社会、情感和文化成果的影响。该系统将由服务不足的语言社区、部落、个人和对提高识字感兴趣的组织获得许可，收入来自使用课程开发人员和专家系统开发人员共享的专家系统开发的移动应用程序产品。SBIR第一阶段项目将开发和测试一个基于知识的专家系统，其中包括早期识字研究；语言分析，为基于语音的早期识字课程开发可解码文本提供循证建议；循证教学和形成性评估战略；课程开发知识；用户界面/用户体验最佳做法；发音反馈的自然语言处理；以及数据库和技术技能，以指导那些可能没有知识和技能来开发任何语言的初级扫盲课程的用户。基于研究的最佳实践和方法将通过分析文本来结合，以创建声音/字母和单词、它们的频率以及每个声音/单词前后的声音和单词的列表。从这些列表中，系统将根据语音和单词的最佳排序规则生成特定于语言的建议，以便学习以另一种语言进行解码。尽管英语解码所需的一些循证指南可能不适用于语音更规则的语言，但大多数指南预计都会适用。英语的语音规则不如许多服务不足的语言。这些规则将指导建议，基于知识的专家系统的用户可以从中选择序列声音、单词和短语，以编写可解码的、相关的文本和文化相关的故事，用于开始扫盲课程。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.