SBIR Phase I: PeTeS: Personalized Text Simplification For English Language Learners

SBIR 第一阶段：PeTeS：针对英语学习者的个性化文本简化

• 批准号: 1843807
• 负责人: Yevgen Borodin
• 金额: $ 22.5万
• 依托单位: Charmtech Labs LLC
• 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: 2019-02-01 至 2019-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1843807&HistoricalAwards=false
• 关键词: SBIR; Phase; PeTeS; Personalized; Text

This SBIR Phase I project seeks to develop a novel text simplification technology that will personalize text to the reading level of students. There is a demand for such tools in inclusive and integrated K- 12 classrooms to cater to the needs of students with varying reading levels. This is especially pertinent to English language learners (Els), international students, and Special Education students with learning disabilities such as dyslexia, ADHD, and other cognitive impairments that impede their reading abilities. Existing tools offer one-size-fits-all solutions offering no control over the simplification process. The proposed Personalized Text Simplifier (PeTeS) will adapt texts to the reading levels of individual students, thereby filling a much-needed gap in the marketplace. With over 60% of U.S. K-12 students reading below grade level, the broader impact of the proposed technology will be in improving the literacy of a diverse population. The expected outcomes of using PeTeS will be improved vocabulary acquisition and improved reading and comprehension of texts by ELs and international students. Using PeTeS for reading may lead to better grades and higher graduation rates. PeTeS will also save teachers time on not having to explain texts or translate for students. PeTeS, will complement the instructor and provide additional support to ELs and international students, especially, in content areas, where these students have very little support.The proposed PeTeS is envisioned to be an adaptive reading assistant for personalizing instruction. The key innovation of PeTeS is in the application of natural language processing algorithms to perform automatic text simplification to dynamically meet specific reading levels - simplification being defined as an adaptation of any given text in a way that maximizes the likelihood that the student will understand its content. The key idea here is to replace a word that is presumed to be not known by the student with a word that is presumed to be known, i.e., the replacement criteria is the student?s knowledge and not the word complexity. Towards that, the proposed PeTeS technology will maintain a student knowledge model representing the reading level of the student. PeTeS will rely on the model not only to simplify the text to the student's level and improve comprehension, but also to challenge the student to learn unfamiliar words while reading whatever they need to read.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.

SBIR 第一阶段项目旨在开发一种新颖的文本简化技术，根据学生的阅读水平个性化文本。包容性和综合性的 K-12 教室需要此类工具，以满足不同阅读水平学生的需求。这对于有学习障碍（如阅读障碍、多动症和其他妨碍阅读能力的认知障碍）的英语学习者 (Els)、国际学生和特殊教育学生尤其重要。现有工具提供一刀切的解决方案，无法控制简化过程。拟议的个性化文本简化器（PeTeS）将使文本适应个别学生的阅读水平，从而填补市场急需的空白。由于超过 60% 的美国 K-12 学生的阅读水平低于年级水平，因此拟议技术的更广泛影响将是提高不同人群的读写能力。使用 PeTeS 的预期成果将是提高 EL 和国际学生的词汇习得以及文本阅读和理解能力。使用 PeTeS 进行阅读可能会带来更好的成绩和更高的毕业率。 PeTeS 还可以节省教师的时间，无需为学生解释课文或翻译。 PeTeS 将补充教师的不足，并为 EL 和国际学生提供额外的支持，特别是在这些学生几乎没有支持的内容领域。拟议的 PeTeS 预计将成为一种自适应阅读助手，用于个性化教学。 PeTeS 的关键创新在于应用自然语言处理算法来执行自动文本简化，以动态满足特定的阅读水平 - 简化被定义为以最大限度地提高学生理解其内容的可能性的方式对任何给定文本进行调整。这里的关键思想是用假定已知的单词替换假定学生不知道的单词，即替换标准是学生的知识而不是单词复杂性。为此，拟议的 PeTeS 技术将维护一个代表学生阅读水平的学生知识模型。 PeTeS 将依靠该模型不仅将文本简化到学生的水平并提高理解能力，而且还挑战学生在阅读他们需要阅读的任何内容时学习不熟悉的单词。该奖项反映了 NSF 的法定使命，并被认为是值得的通过使用基金会的智力优势和更广泛的影响审查标准进行评估来提供支持。